A case of EDTA-dependent pseudothrombocytopenia: simple recognition of an underdiagnosed and misleading phenomenon

PubMed Central

2014-01-01

Background EDTA-dependent pseudothrombocytopenia (EDTA-PTCP) is a common laboratory phenomenon with a prevalence ranging from 0.1-2% in hospitalized patients to 15-17% in outpatients evaluated for isolated thrombocytopenia. Despite its harmlessness, EDTA-PTCP frequently leads to time-consuming, costly and even invasive diagnostic investigations. EDTA-PTCP is often overlooked because blood smears are not evaluated visually in routine practice and histograms as well as warning flags of hematology analyzers are not interpreted correctly. Nonetheless, EDTA-PTCP may be diagnosed easily even by general practitioners without any experiences in blood film examinations. This is the first report illustrating the typical patterns of a platelet (PLT) and white blood cell (WBC) histograms of hematology analyzers. Case presentation A 37-year-old female patient of Caucasian origin was referred with suspected acute leukemia and the crew of the emergency unit arranged extensive investigations for work-up. However, examination of EDTA blood sample revealed atypical lymphocytes and an isolated thrombocytopenia together with typical patterns of WBC and PLT histograms: a serrated curve of the platelet histogram and a peculiar peak on the left side of the WBC histogram. EDTA-PTCP was confirmed by a normal platelet count when examining citrated blood. Conclusion Awareness of typical PLT and WBC patterns may alert to the presence of EDTA-PTCP in routine laboratory practice helping to avoid unnecessary investigations and over-treatment. PMID:24808761

Characteristics of random inlet pressure fluctuations during flights of F-111A airplane

NASA Technical Reports Server (NTRS)

Costakis, W. G.

1977-01-01

Compressor face dynamic total pressures from four F-111 flights were analyzed. Statistics of the nonstationary data were investigated by analyzing the data in a quasi-stationary manner. Changes in the character of the dynamic signal are investigated as functions of flight conditions, time in flight, and location at the compressor face. The results, which are presented in the form of rms values, histograms, and power spectrum plots, show that the shape of the power spectra remains relatively flat while the histograms have an approximate normal distribution.

Variations of attractors and wavelet spectra of the immunofluorescence distributions for women in the pregnant period

NASA Astrophysics Data System (ADS)

Galich, Nikolay E.

2008-07-01

Communication contains the description of the immunology data treatment. New nonlinear methods of immunofluorescence statistical analysis of peripheral blood neutrophils have been developed. We used technology of respiratory burst reaction of DNA fluorescence in the neutrophils cells nuclei due to oxidative activity. The histograms of photon count statistics the radiant neutrophils populations' in flow cytometry experiments are considered. Distributions of the fluorescence flashes frequency as functions of the fluorescence intensity are analyzed. Statistic peculiarities of histograms set for women in the pregnant period allow dividing all histograms on the three classes. The classification is based on three different types of smoothing and long-range scale averaged immunofluorescence distributions, their bifurcation and wavelet spectra. Heterogeneity peculiarities of long-range scale immunofluorescence distributions and peculiarities of wavelet spectra allow dividing all histograms on three groups. First histograms group belongs to healthy donors. Two other groups belong to donors with autoimmune and inflammatory diseases. Some of the illnesses are not diagnosed by standards biochemical methods. Medical standards and statistical data of the immunofluorescence histograms for identifications of health and illnesses are interconnected. Peculiarities of immunofluorescence for women in pregnant period are classified. Health or illness criteria are connected with statistics features of immunofluorescence histograms. Neutrophils populations' fluorescence presents the sensitive clear indicator of health status.

Potential of MR histogram analyses for prediction of response to chemotherapy in patients with colorectal hepatic metastases.

PubMed

Liang, He-Yue; Huang, Ya-Qin; Yang, Zhao-Xia; Ying-Ding; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-07-01

To determine if magnetic resonance imaging (MRI) histogram analyses can help predict response to chemotherapy in patients with colorectal hepatic metastases by using response evaluation criteria in solid tumours (RECIST1.1) as the reference standard. Standard MRI including diffusion-weighted imaging (b=0, 500 s/mm(2)) was performed before chemotherapy in 53 patients with colorectal hepatic metastases. Histograms were performed for apparent diffusion coefficient (ADC) maps, arterial, and portal venous phase images; thereafter, mean, percentiles (1st, 10th, 50th, 90th, 99th), skewness, kurtosis, and variance were generated. Quantitative histogram parameters were compared between responders (partial and complete response, n=15) and non-responders (progressive and stable disease, n=38). Receiver operator characteristics (ROC) analyses were further analyzed for the significant parameters. The mean, 1st percentile, 10th percentile, 50th percentile, 90th percentile, 99th percentile of the ADC maps were significantly lower in responding group than that in non-responding group (p=0.000-0.002) with area under the ROC curve (AUCs) of 0.76-0.82. The histogram parameters of arterial and portal venous phase showed no significant difference (p>0.05) between the two groups. Histogram-derived parameters for ADC maps seem to be a promising tool for predicting response to chemotherapy in patients with colorectal hepatic metastases. • ADC histogram analyses can potentially predict chemotherapy response in colorectal liver metastases. • Lower histogram-derived parameters (mean, percentiles) for ADC tend to have good response. • MR enhancement histogram analyses are not reliable to predict response.

Quantitative histogram analysis of images

NASA Astrophysics Data System (ADS)

Holub, Oliver; Ferreira, Sérgio T.

2006-11-01

A routine for histogram analysis of images has been written in the object-oriented, graphical development environment LabVIEW. The program converts an RGB bitmap image into an intensity-linear greyscale image according to selectable conversion coefficients. This greyscale image is subsequently analysed by plots of the intensity histogram and probability distribution of brightness, and by calculation of various parameters, including average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of the histogram and the median of the probability distribution. The program allows interactive selection of specific regions of interest (ROI) in the image and definition of lower and upper threshold levels (e.g., to permit the removal of a constant background signal). The results of the analysis of multiple images can be conveniently saved and exported for plotting in other programs, which allows fast analysis of relatively large sets of image data. The program file accompanies this manuscript together with a detailed description of two application examples: The analysis of fluorescence microscopy images, specifically of tau-immunofluorescence in primary cultures of rat cortical and hippocampal neurons, and the quantification of protein bands by Western-blot. The possibilities and limitations of this kind of analysis are discussed. Program summaryTitle of program: HAWGC Catalogue identifier: ADXG_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXG_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computers: Mobile Intel Pentium III, AMD Duron Installations: No installation necessary—Executable file together with necessary files for LabVIEW Run-time engine Operating systems or monitors under which the program has been tested: WindowsME/2000/XP Programming language used: LabVIEW 7.0 Memory required to execute with typical data:˜16MB for starting and ˜160MB used for loading of an image No. of bits in a word: 32 No. of processors used: 1 Has the code been vectorized or parallelized?: No No of lines in distributed program, including test data, etc.:138 946 No. of bytes in distributed program, including test data, etc.:15 166 675 Distribution format: tar.gz Nature of physical problem: Quantification of image data (e.g., for discrimination of molecular species in gels or fluorescent molecular probes in cell cultures) requires proprietary or complex software packages, which might not include the relevant statistical parameters or make the analysis of multiple images a tedious procedure for the general user. Method of solution: Tool for conversion of RGB bitmap image into luminance-linear image and extraction of luminance histogram, probability distribution, and statistical parameters (average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of histogram and median of probability distribution) with possible selection of region of interest (ROI) and lower and upper threshold levels. Restrictions on the complexity of the problem: Does not incorporate application-specific functions (e.g., morphometric analysis) Typical running time: Seconds (depending on image size and processor speed) Unusual features of the program: None

SU-F-J-94: Development of a Plug-in Based Image Analysis Tool for Integration Into Treatment Planning

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

Owen, D; Anderson, C; Mayo, C

Purpose: To extend the functionality of a commercial treatment planning system (TPS) to support (i) direct use of quantitative image-based metrics within treatment plan optimization and (ii) evaluation of dose-functional volume relationships to assist in functional image adaptive radiotherapy. Methods: A script was written that interfaces with a commercial TPS via an Application Programming Interface (API). The script executes a program that performs dose-functional volume analyses. Written in C#, the script reads the dose grid and correlates it with image data on a voxel-by-voxel basis through API extensions that can access registration transforms. A user interface was designed through WinFormsmore » to input parameters and display results. To test the performance of this program, image- and dose-based metrics computed from perfusion SPECT images aligned to the treatment planning CT were generated, validated, and compared. Results: The integration of image analysis information was successfully implemented as a plug-in to a commercial TPS. Perfusion SPECT images were used to validate the calculation and display of image-based metrics as well as dose-intensity metrics and histograms for defined structures on the treatment planning CT. Various biological dose correction models, custom image-based metrics, dose-intensity computations, and dose-intensity histograms were applied to analyze the image-dose profile. Conclusion: It is possible to add image analysis features to commercial TPSs through custom scripting applications. A tool was developed to enable the evaluation of image-intensity-based metrics in the context of functional targeting and avoidance. In addition to providing dose-intensity metrics and histograms that can be easily extracted from a plan database and correlated with outcomes, the system can also be extended to a plug-in optimization system, which can directly use the computed metrics for optimization of post-treatment tumor or normal tissue response models. Supported by NIH - P01 - CA059827.« less

Program for the analysis of time series. [by means of fast Fourier transform algorithm

NASA Technical Reports Server (NTRS)

Brown, T. J.; Brown, C. G.; Hardin, J. C.

1974-01-01

A digital computer program for the Fourier analysis of discrete time data is described. The program was designed to handle multiple channels of digitized data on general purpose computer systems. It is written, primarily, in a version of FORTRAN 2 currently in use on CDC 6000 series computers. Some small portions are written in CDC COMPASS, an assembler level code. However, functional descriptions of these portions are provided so that the program may be adapted for use on any facility possessing a FORTRAN compiler and random-access capability. Properly formatted digital data are windowed and analyzed by means of a fast Fourier transform algorithm to generate the following functions: (1) auto and/or cross power spectra, (2) autocorrelations and/or cross correlations, (3) Fourier coefficients, (4) coherence functions, (5) transfer functions, and (6) histograms.

Neutron camera employing row and column summations

DOEpatents

Clonts, Lloyd G.; Diawara, Yacouba; Donahue, Jr, Cornelius; Montcalm, Christopher A.; Riedel, Richard A.; Visscher, Theodore

2016-06-14

For each photomultiplier tube in an Anger camera, an R.times.S array of preamplifiers is provided to detect electrons generated within the photomultiplier tube. The outputs of the preamplifiers are digitized to measure the magnitude of the signals from each preamplifier. For each photomultiplier tube, a corresponding summation circuitry including R row summation circuits and S column summation circuits numerically add the magnitudes of the signals from preamplifiers for each row and for each column to generate histograms. For a P.times.Q array of photomultiplier tubes, P.times.Q summation circuitries generate P.times.Q row histograms including R entries and P.times.Q column histograms including S entries. The total set of histograms include P.times.Q.times.(R+S) entries, which can be analyzed by a position calculation circuit to determine the locations of events (detection of a neutron).

ADC histogram analysis of muscle lymphoma - Correlation with histopathology in a rare entity.

PubMed

Meyer, Hans-Jonas; Pazaitis, Nikolaos; Surov, Alexey

2018-06-21

Diffusion weighted imaging (DWI) is able to reflect histopathology architecture. A novel imaging approach, namely histogram analysis, is used to further characterize lesion on MRI. The purpose of this study is to correlate histogram parameters derived from apparent diffusion coefficient- (ADC) maps with histopathology parameters in muscle lymphoma. Eight patients (mean age 64.8 years, range 45-72 years) with histopathologically confirmed muscle lymphoma were retrospectively identified. Cell count, total nucleic and average nucleic areas were estimated using ImageJ. Additionally, Ki67-index was calculated. DWI was obtained on a 1.5T scanner by using the b values of 0 and 1000 s/mm2. Histogram analysis was performed as a whole lesion measurement by using a custom-made Matlabbased application. The correlation analysis revealed statistically significant correlation between cell count and ADCmean (p=-0.76, P=0.03) as well with ADCp75 (p=-0.79, P=0.02). Kurtosis and entropy correlated with average nucleic area (p=-0.81, P=0.02, p=0.88, P=0.007, respectively). None of the analyzed ADC parameters correlated with total nucleic area and with Ki67-index. This study identified significant correlations between cellularity and histogram parameters derived from ADC maps in muscle lymphoma. Thus, histogram analysis parameters reflect histopathology in muscle tumors. Advances in knowledge: Whole lesion ADC histogram analysis is able to reflect histopathology parameters in muscle lymphomas.

Delay, change and bifurcation of the immunofluorescence distribution attractors in health statuses diagnostics and in medical treatment

NASA Astrophysics Data System (ADS)

Galich, Nikolay E.; Filatov, Michael V.

2008-07-01

Communication contains the description of the immunology experiments and the experimental data treatment. New nonlinear methods of immunofluorescence statistical analysis of peripheral blood neutrophils have been developed. We used technology of respiratory burst reaction of DNA fluorescence in the neutrophils cells nuclei due to oxidative activity. The histograms of photon count statistics the radiant neutrophils populations' in flow cytometry experiments are considered. Distributions of the fluorescence flashes frequency as functions of the fluorescence intensity are analyzed. Statistic peculiarities of histograms set for healthy and unhealthy donors allow dividing all histograms on the three classes. The classification is based on three different types of smoothing and long-range scale averaged immunofluorescence distributions and their bifurcation. Heterogeneity peculiarities of long-range scale immunofluorescence distributions allow dividing all histograms on three groups. First histograms group belongs to healthy donors. Two other groups belong to donors with autoimmune and inflammatory diseases. Some of the illnesses are not diagnosed by standards biochemical methods. Medical standards and statistical data of the immunofluorescence histograms for identifications of health and illnesses are interconnected. Possibilities and alterations of immunofluorescence statistics in registration, diagnostics and monitoring of different diseases in various medical treatments have been demonstrated. Health or illness criteria are connected with statistics features of immunofluorescence histograms. Neutrophils populations' fluorescence presents the sensitive clear indicator of health status.

Adaptive Processing of RADARSAT-1 Fine Mode Data: Ship Parameter Estimation

DTIC Science & Technology

2007-03-01

53 Figure 60: D7S1, the 63 m long freighter “ Germa ” is one of the smallest ships in the data set. .. 53 Figure 61: D6S1...5 10 15 20 25 30 length [m] N um be r of s hi ps Figure 1: Length histogram of analyzed ships according to the AIS data. 8 DRDC Ottawa TM 2007...053 0 50 100 150 200 250 300 350 400 0 5 10 15 20 25 θ [°] N um be r of s hi ps Figure 2: Aspect angle histogram of analyzed ships

MC-TESTER v. 1.23: A universal tool for comparisons of Monte Carlo predictions for particle decays in high energy physics

NASA Astrophysics Data System (ADS)

Davidson, N.; Golonka, P.; Przedziński, T.; Waş, Z.

2011-03-01

Theoretical predictions in high energy physics are routinely provided in the form of Monte Carlo generators. Comparisons of predictions from different programs and/or different initialization set-ups are often necessary. MC-TESTER can be used for such tests of decays of intermediate states (particles or resonances) in a semi-automated way. Since 2002 new functionalities were introduced into the package. In particular, it now works with the HepMC event record, the standard for C++ programs. The complete set-up for benchmarking the interfaces, such as interface between τ-lepton production and decay, including QED bremsstrahlung effects is shown. The example is chosen to illustrate the new options introduced into the program. From the technical perspective, our paper documents software updates and supplements previous documentation. As in the past, our test consists of two steps. Distinct Monte Carlo programs are run separately; events with decays of a chosen particle are searched, and information is stored by MC-TESTER. Then, at the analysis step, information from a pair of runs may be compared and represented in the form of tables and plots. Updates introduced in the program up to version 1.24.4 are also documented. In particular, new configuration scripts or script to combine results from multitude of runs into single information file to be used in analysis step are explained. Program summaryProgram title: MC-TESTER, version 1.23 and version 1.24.4 Catalog identifier: ADSM_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSM_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 250 548 No. of bytes in distributed program, including test data, etc.: 4 290 610 Distribution format: tar.gz Programming language: C++, FORTRAN77 Tested and compiled with: gcc 3.4.6, 4.2.4 and 4.3.2 with g77/gfortran Computer: Tested on various platforms Operating system: Tested on operating systems: Linux SLC 4.6 and SLC 5, Fedora 8, Ubuntu 8.2 etc. Classification: 11.9 External routines: HepMC ( https://savannah.cern.ch/projects/hepmc/), PYTHIA8 ( http://home.thep.lu.se/~torbjorn/Pythia.html), LaTeX ( http://www.latex-project.org/) Catalog identifier of previous version: ADSM_v1_0 Journal reference of previous version: Comput. Phys. Comm. 157 (2004) 39 Does the new version supersede the previous version?: Yes Nature of problem: The decays of individual particles are well defined modules of a typical Monte Carlo program chain in high energy physics. A fast, semi-automatic way of comparing results from different programs is often desirable for the development of new programs, in order to check correctness of the installations or for discussion of uncertainties. Solution method: A typical HEP Monte Carlo program stores the generated events in event records such as HepMC, HEPEVT or PYJETS. MC-TESTER scans, event by event, the contents of the record and searches for the decays of the particle under study. The list of the found decay modes is successively incremented and histograms of all invariant masses which can be calculated from the momenta of the particle decay products are defined and filled. The outputs from the two runs of distinct programs can be later compared. A booklet of comparisons is created: for every decay channel, all histograms present in the two outputs are plotted and parameter quantifying shape difference is calculated. Its maximum over every decay channel is printed in the summary table. Reasons for new version: Interface for HepMC Event Record is introduced. Setup for benchmarking the interfaces, such as τ-lepton production and decay, including QED bremsstrahlung effects is introduced as well. This required significant changes in the algorithm. As a consequence, a new version of the code was introduced. Restrictions: Only the first 200 decay channels that were found will initialize histograms and if the multiplicity of decay products in a given channel was larger than 7, histograms will not be created for that channel. Additional comments: New features: HepMC interface, use of lists in definition of histograms and decay channels, filters for decay products or secondary decays to be omitted, bug fixing, extended flexibility in representation of program output, installation configuration scripts, merging multiple output files from separate generations. Running time: Varies substantially with the analyzed decay particle, but generally speed estimation of the old version remains valid. On a PC/Linux with 2.0 GHz processors MC-TESTER increases the run time of the τ-lepton Monte Carlo program TAUOLA by 4.0 seconds for every 100 000 analyzed events (generation itself takes 26 seconds). The analysis step takes 13 seconds; LATEX processing takes additionally 10 seconds. Generation step runs may be executed simultaneously on multiprocessor machines.

[Image Feature Extraction and Discriminant Analysis of Xinjiang Uygur Medicine Based on Color Histogram].

PubMed

Hamit, Murat; Yun, Weikang; Yan, Chuanbo; Kutluk, Abdugheni; Fang, Yang; Alip, Elzat

2015-06-01

Image feature extraction is an important part of image processing and it is an important field of research and application of image processing technology. Uygur medicine is one of Chinese traditional medicine and researchers pay more attention to it. But large amounts of Uygur medicine data have not been fully utilized. In this study, we extracted the image color histogram feature of herbal and zooid medicine of Xinjiang Uygur. First, we did preprocessing, including image color enhancement, size normalizition and color space transformation. Then we extracted color histogram feature and analyzed them with statistical method. And finally, we evaluated the classification ability of features by Bayes discriminant analysis. Experimental results showed that high accuracy for Uygur medicine image classification was obtained by using color histogram feature. This study would have a certain help for the content-based medical image retrieval for Xinjiang Uygur medicine.

Histogram analysis parameters of apparent diffusion coefficient reflect tumor cellularity and proliferation activity in head and neck squamous cell carcinoma

PubMed Central

Winter, Karsten; Richter, Cindy; Hoehn, Anna-Kathrin

2018-01-01

Our purpose was to analyze associations between apparent diffusion coefficient (ADC) histogram analysis parameters and histopathologicalfeatures in head and neck squamous cell carcinoma (HNSCC). The study involved 32 patients with primary HNSCC. For every tumor, the following histogram analysis parameters were calculated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, P10, P25, P75, P90, kurtosis, skewness, and entropy. Furthermore, proliferation index KI 67, cell count, total and average nucleic areas were estimated. Spearman's correlation coefficient (p) was used to analyze associations between investigated parameters. In overall sample, all ADC values showed moderate inverse correlations with KI 67. All ADC values except ADCmax correlated inversely with tumor cellularity. Slightly correlations were identified between total/average nucleic area and ADCmean, ADCmin, ADCmedian, and P25. In G1/2 tumors, only ADCmode correlated well with Ki67. No statistically significant correlations between ADC parameters and cellularity were found. In G3 tumors, Ki 67 correlated with all ADC parameters except ADCmode. Cell count correlated well with all ADC parameters except ADCmax. Total nucleic area correlated inversely with ADCmean, ADCmin, ADCmedian, P25, and P90. ADC histogram parameters reflect proliferation potential and cellularity in HNSCC. The associations between histopathology and imaging depend on tumor grading. PMID:29805759

Histogram Analysis of Diffusion Weighted Imaging at 3T is Useful for Prediction of Lymphatic Metastatic Spread, Proliferative Activity, and Cellularity in Thyroid Cancer.

PubMed

Schob, Stefan; Meyer, Hans Jonas; Dieckow, Julia; Pervinder, Bhogal; Pazaitis, Nikolaos; Höhn, Anne Kathrin; Garnov, Nikita; Horvath-Rizea, Diana; Hoffmann, Karl-Titus; Surov, Alexey

2017-04-12

Pre-surgical diffusion weighted imaging (DWI) is increasingly important in the context of thyroid cancer for identification of the optimal treatment strategy. It has exemplarily been shown that DWI at 3T can distinguish undifferentiated from well-differentiated thyroid carcinoma, which has decisive implications for the magnitude of surgery. This study used DWI histogram analysis of whole tumor apparent diffusion coefficient (ADC) maps. The primary aim was to discriminate thyroid carcinomas which had already gained the capacity to metastasize lymphatically from those not yet being able to spread via the lymphatic system. The secondary aim was to reflect prognostically important tumor-biological features like cellularity and proliferative activity with ADC histogram analysis. Fifteen patients with follicular-cell derived thyroid cancer were enrolled. Lymph node status, extent of infiltration of surrounding tissue, and Ki-67 and p53 expression were assessed in these patients. DWI was obtained in a 3T system using b values of 0, 400, and 800 s/mm². Whole tumor ADC volumes were analyzed using a histogram-based approach. Several ADC parameters showed significant correlations with immunohistopathological parameters. Most importantly, ADC histogram skewness and ADC histogram kurtosis were able to differentiate between nodal negative and nodal positive thyroid carcinoma. histogram analysis of whole ADC tumor volumes has the potential to provide valuable information on tumor biology in thyroid carcinoma. However, further studies are warranted.

Histogram Analysis of Diffusion Weighted Imaging at 3T is Useful for Prediction of Lymphatic Metastatic Spread, Proliferative Activity, and Cellularity in Thyroid Cancer

PubMed Central

Schob, Stefan; Meyer, Hans Jonas; Dieckow, Julia; Pervinder, Bhogal; Pazaitis, Nikolaos; Höhn, Anne Kathrin; Garnov, Nikita; Horvath-Rizea, Diana; Hoffmann, Karl-Titus; Surov, Alexey

2017-01-01

Pre-surgical diffusion weighted imaging (DWI) is increasingly important in the context of thyroid cancer for identification of the optimal treatment strategy. It has exemplarily been shown that DWI at 3T can distinguish undifferentiated from well-differentiated thyroid carcinoma, which has decisive implications for the magnitude of surgery. This study used DWI histogram analysis of whole tumor apparent diffusion coefficient (ADC) maps. The primary aim was to discriminate thyroid carcinomas which had already gained the capacity to metastasize lymphatically from those not yet being able to spread via the lymphatic system. The secondary aim was to reflect prognostically important tumor-biological features like cellularity and proliferative activity with ADC histogram analysis. Fifteen patients with follicular-cell derived thyroid cancer were enrolled. Lymph node status, extent of infiltration of surrounding tissue, and Ki-67 and p53 expression were assessed in these patients. DWI was obtained in a 3T system using b values of 0, 400, and 800 s/mm2. Whole tumor ADC volumes were analyzed using a histogram-based approach. Several ADC parameters showed significant correlations with immunohistopathological parameters. Most importantly, ADC histogram skewness and ADC histogram kurtosis were able to differentiate between nodal negative and nodal positive thyroid carcinoma. Conclusions: histogram analysis of whole ADC tumor volumes has the potential to provide valuable information on tumor biology in thyroid carcinoma. However, further studies are warranted. PMID:28417929

Enhancing tumor apparent diffusion coefficient histogram skewness stratifies the postoperative survival in recurrent glioblastoma multiforme patients undergoing salvage surgery.

PubMed

Zolal, Amir; Juratli, Tareq A; Linn, Jennifer; Podlesek, Dino; Sitoci Ficici, Kerim Hakan; Kitzler, Hagen H; Schackert, Gabriele; Sobottka, Stephan B; Rieger, Bernhard; Krex, Dietmar

2016-05-01

Objective To determine the value of apparent diffusion coefficient (ADC) histogram parameters for the prediction of individual survival in patients undergoing surgery for recurrent glioblastoma (GBM) in a retrospective cohort study. Methods Thirty-one patients who underwent surgery for first recurrence of a known GBM between 2008 and 2012 were included. The following parameters were collected: age, sex, enhancing tumor size, mean ADC, median ADC, ADC skewness, ADC kurtosis and fifth percentile of the ADC histogram, initial progression free survival (PFS), extent of second resection and further adjuvant treatment. The association of these parameters with survival and PFS after second surgery was analyzed using log-rank test and Cox regression. Results Using log-rank test, ADC histogram skewness of the enhancing tumor was significantly associated with both survival (p = 0.001) and PFS after second surgery (p = 0.005). Further parameters associated with prolonged survival after second surgery were: gross total resection at second surgery (p = 0.026), tumor size (0.040) and third surgery (p = 0.003). In the multivariate Cox analysis, ADC histogram skewness was shown to be an independent prognostic factor for survival after second surgery. Conclusion ADC histogram skewness of the enhancing lesion, enhancing lesion size, third surgery, as well as gross total resection have been shown to be associated with survival following the second surgery. ADC histogram skewness was an independent prognostic factor for survival in the multivariate analysis.

SU-C-207A-07: Cumulative 18F-FDG Uptake Histogram Relative to Radiation Dose Volume Histogram of Lung After IMRT Or PSPT and Their Association with Radiation Pneumonitis

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

Shusharina, N; Choi, N; Bortfeld, T

2016-06-15

Purpose: To determine whether the difference in cumulative 18F-FDG uptake histogram of lung treated with either IMRT or PSPT is associated with radiation pneumonitis (RP) in patients with inoperable stage II and III NSCLC. Methods: We analyzed 24 patients from a prospective randomized trial to compare IMRT (n=12) with vs. PSPT (n=12) for inoperable NSCLC. All patients underwent PET-CT imaging between 35 and 88 days post-therapy. Post-treatment PET-CT was aligned with planning 4D CT to establish a voxel-to-voxel correspondence between post-treatment PET and planning dose images. 18F-FDG uptake as a function of radiation dose to normal lung was obtained formore » each patient. Distribution of the standard uptake value (SUV) was analyzed using a volume histogram method. The image quantitative characteristics and DVH measures were correlated with clinical symptoms of pneumonitis. Results: Patients with RP were present in both groups: 5 in the IMRT and 6 in the PSPT. The analysis of cumulative SUV histograms showed significantly higher relative volumes of the normal lung having higher SUV uptake in the PSPT patients for both symptomatic and asymptomatic cases (VSUV=2: 10% for IMRT vs 16% for proton RT and VSUV=1: 10% for IMRT vs 23% for proton RT). In addition, the SUV histograms for symptomatic cases in PSPT patients exhibited a significantly longer tail at the highest SUV. The absolute volume of the lung receiving the dose >70 Gy was larger in the PSPT patients. Conclusion: 18F-FDG uptake – radiation dose response correlates with RP in both groups of patients by means of the linear regression slope. SUV is higher for the PSPT patients for both symptomatic and asymptomatic cases. Higher uptake after PSPT patients is explained by larger volumes of the lung receiving high radiation dose.« less

Hybrid Histogram Descriptor: A Fusion Feature Representation for Image Retrieval.

PubMed

Feng, Qinghe; Hao, Qiaohong; Chen, Yuqi; Yi, Yugen; Wei, Ying; Dai, Jiangyan

2018-06-15

Currently, visual sensors are becoming increasingly affordable and fashionable, acceleratingly the increasing number of image data. Image retrieval has attracted increasing interest due to space exploration, industrial, and biomedical applications. Nevertheless, designing effective feature representation is acknowledged as a hard yet fundamental issue. This paper presents a fusion feature representation called a hybrid histogram descriptor (HHD) for image retrieval. The proposed descriptor comprises two histograms jointly: a perceptually uniform histogram which is extracted by exploiting the color and edge orientation information in perceptually uniform regions; and a motif co-occurrence histogram which is acquired by calculating the probability of a pair of motif patterns. To evaluate the performance, we benchmarked the proposed descriptor on RSSCN7, AID, Outex-00013, Outex-00014 and ETHZ-53 datasets. Experimental results suggest that the proposed descriptor is more effective and robust than ten recent fusion-based descriptors under the content-based image retrieval framework. The computational complexity was also analyzed to give an in-depth evaluation. Furthermore, compared with the state-of-the-art convolutional neural network (CNN)-based descriptors, the proposed descriptor also achieves comparable performance, but does not require any training process.

LACIE performance predictor final operational capability program description, volume 2

NASA Technical Reports Server (NTRS)

1976-01-01

Given the swath table files, the segment set for one country and cloud cover data, the SAGE program determines how many times and under what conditions each segment is accessed by satellites. The program writes a record for each segment on a data file which contains the pertinent acquisition data. The weather data file can also be generated from a NASA supplied tape. The Segment Acquisition Selector Program (SACS) selects data from the segment reference file based upon data input manually and from a crop window file. It writes the extracted data to a data acquisition file and prints two summary reports. The POUT program reads from associated LACIE files and produces printed reports. The major types of reports that can be produced are: (1) Substrate Reference Data Reports, (2) Population Mean, Standard Deviation and Histogram Reports, (3) Histograms of Monte Carlo Statistics Reports, and (4) Frequency of Sample Segment Acquisitions Reports.

Histogram analysis parameters of apparent diffusion coefficient reflect tumor cellularity and proliferation activity in head and neck squamous cell carcinoma.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Winter, Karsten; Richter, Cindy; Hoehn, Anna-Kathrin

2018-05-04

Our purpose was to analyze associations between apparent diffusion coefficient (ADC) histogram analysis parameters and histopathologicalfeatures in head and neck squamous cell carcinoma (HNSCC). The study involved 32 patients with primary HNSCC. For every tumor, the following histogram analysis parameters were calculated: ADCmean, ADCmax, ADC min , ADC median , ADC mode , P10, P25, P75, P90, kurtosis, skewness, and entropy. Furthermore, proliferation index KI 67, cell count, total and average nucleic areas were estimated. Spearman's correlation coefficient (p) was used to analyze associations between investigated parameters. In overall sample, all ADC values showed moderate inverse correlations with KI 67. All ADC values except ADCmax correlated inversely with tumor cellularity. Slightly correlations were identified between total/average nucleic area and ADC mean , ADC min , ADC median , and P25. In G1/2 tumors, only ADCmode correlated well with Ki67. No statistically significant correlations between ADC parameters and cellularity were found. In G3 tumors, Ki 67 correlated with all ADC parameters except ADCmode. Cell count correlated well with all ADC parameters except ADCmax. Total nucleic area correlated inversely with ADC mean , ADC min , ADC median , P25, and P90. ADC histogram parameters reflect proliferation potential and cellularity in HNSCC. The associations between histopathology and imaging depend on tumor grading.

Discussion on the 3D visualizing of 1:200 000 geological map

NASA Astrophysics Data System (ADS)

Wang, Xiaopeng

2018-01-01

Using United States National Aeronautics and Space Administration Shuttle Radar Topography Mission (SRTM) terrain data as digital elevation model (DEM), overlap scanned 1:200 000 scale geological map, program using Direct 3D of Microsoft with C# computer language, the author realized the three-dimensional visualization of the standard division geological map. User can inspect the regional geology content with arbitrary angle, rotating, roaming, and can examining the strata synthetical histogram, map section and legend at any moment. This will provide an intuitionistic analyzing tool for the geological practitioner to do structural analysis with the assistant of landform, dispose field exploration route etc.

DYAD: A Computer Program for the Analysis of Interpersonal Communication

ERIC Educational Resources Information Center

Fogel, Daniel S.

1978-01-01

A computer program which generates descriptions of conversational patterns of dyads based on sound-silence data is described. Input consists of talk/no-talk designations; output consists of descriptive matrices, histograms, and individual talk parameters. (Author/JKS)

SU-F-R-50: Radiation-Induced Changes in CT Number Histogram During Chemoradiation Therapy for Pancreatic Cancer

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

Chen, X; Schott, D; Song, Y

Purpose: In an effort of early assessment of treatment response, we investigate radiation induced changes in CT number histogram of GTV during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Diagnostic-quality CT data acquired daily during routine CT-guided CRT using a CT-on-rails for 20 pancreatic head cancer patients were analyzed. All patients were treated with a radiation dose of 50.4 in 28 fractions. On each daily CT set, the contours of the pancreatic head and the spinal cord were delineated. The Hounsfiled Units (HU) histogram in these contourswere extracted and processed using MATLAB. Eight parameters of the histogrammore » including the mean HU over all the voxels, peak position, volume, standard deviation (SD), skewness, kurtosis, energy, and entropy were calculated for each fraction. The significances were inspected using paired two-tailed t-test and the correlations were analyzed using Spearman rank correlation tests. Results: In general, HU histogram in pancreatic head (but not in spinal cord) changed during the CRT delivery. Changes from the first to the last fraction in mean HU in pancreatic head ranged from −13.4 to 3.7 HU with an average of −4.4 HU, which was significant (P<0.001). Among other quantities, the volume decreased, the skewness increased (less skewed), and the kurtosis decreased (less sharp) during the CRT delivery. The changes of mean HU, volume, skewness, and kurtosis became significant after two weeks of treatment. Patient pathological response status is associated with the changes of SD (ΔSD), i.e., ΔSD= 1.85 (average of 7 patients) for good reponse, −0.08 (average of 6 patients) for moderate and poor response. Conclusion: Significant changes in HU histogram and the histogram-based metrics (e.g., meam HU, skewness, and kurtosis) in tumor were observed during the course of chemoradiation therapy for pancreas cancer. These changes may be potentially used for early assessment of treatment response.« less

Whole lesion histogram analysis of meningiomas derived from ADC values. Correlation with several cellularity parameters, proliferation index KI 67, nucleic content, and membrane permeability.

PubMed

Surov, Alexey; Hamerla, Gordian; Meyer, Hans Jonas; Winter, Karsten; Schob, Stefan; Fiedler, Eckhard

2018-09-01

To analyze several histopathological features and their possible correlations with whole lesion histogram analysis derived from ADC maps in meningioma. The retrospective study involved 36 patients with primary meningiomas. For every tumor, the following histogram analysis parameters of apparent diffusion coefficient (ADC) were calculated: ADC mean , ADC max , ADC min , ADC median , ADC mode , ADC percentiles: P10, P25, P75, P90, as well kurtosis, skewness, and entropy. All measures were performed by two radiologists. Proliferation index KI 67, minimal, maximal and mean cell count, total nucleic area, and expression of water channel aquaporin 4 (AQP4) were estimated. Spearman's correlation coefficient was used to analyze associations between investigated parameters. A perfect interobserver agreement for all ADC values (0.84-0.97) was identified. All ADC values correlated inversely with tumor cellularity with the strongest correlation between P10, P25 and mean cell count (-0.558). KI 67 correlated inversely with all ADC values except ADC min . ADC parameters did not correlate with total nucleic area. All ADC values correlated statistically significant with expression of AQP4. ADC histogram analysis is a valid method with an excellent interobserver agreement. Cellularity parameters and proliferation potential are associated with different ADC values. Membrane permeability may play a greater role for water diffusion than cell count and proliferation activity. Copyright © 2018 Elsevier Inc. All rights reserved.

Automated Weather Observing System (AWOS) Demonstration Program.

DTIC Science & Technology

1984-09-01

month "bur:-in" r "debugging" period and a 10-month ’usefu I life " period. Fhe butrn- in pr i ,J was i sed to establish the Data Acquisition System...Histograms. Histograms provide a graphical means of showing how well the probability distribution of residu : , approaches a normal or Gaussian distribution...Organization Report No. 7- Author’s) Paul .J. O t Brien et al. DOT/FAA/CT-84/20 9. Performing Organlzation Name and Address 10. Work Unit No. (TRAIS

False alarm recognition in hyperspectral gas plume identification

DOEpatents

Conger, James L [San Ramon, CA; Lawson, Janice K [Tracy, CA; Aimonetti, William D [Livermore, CA

2011-03-29

According to one embodiment, a method for analyzing hyperspectral data includes collecting first hyperspectral data of a scene using a hyperspectral imager during a no-gas period and analyzing the first hyperspectral data using one or more gas plume detection logics. The gas plume detection logic is executed using a low detection threshold, and detects each occurrence of an observed hyperspectral signature. The method also includes generating a histogram for all occurrences of each observed hyperspectral signature which is detected using the gas plume detection logic, and determining a probability of false alarm (PFA) for all occurrences of each observed hyperspectral signature based on the histogram. Possibly at some other time, the method includes collecting second hyperspectral data, and analyzing the second hyperspectral data using the one or more gas plume detection logics and the PFA to determine if any gas is present. Other systems and methods are also included.

Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology.

PubMed

Sharma, Harshita; Zerbe, Norman; Klempert, Iris; Hellwich, Olaf; Hufnagl, Peter

2017-11-01

Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning methods for computer-aided classification in H&E stained histopathological whole slide images of gastric carcinoma. An introductory convolutional neural network architecture is proposed for two computerized applications, namely, cancer classification based on immunohistochemical response and necrosis detection based on the existence of tumor necrosis in the tissue. Classification performance of the developed deep learning approach is quantitatively compared with traditional image analysis methods in digital histopathology requiring prior computation of handcrafted features, such as statistical measures using gray level co-occurrence matrix, Gabor filter-bank responses, LBP histograms, gray histograms, HSV histograms and RGB histograms, followed by random forest machine learning. Additionally, the widely known AlexNet deep convolutional framework is comparatively analyzed for the corresponding classification problems. The proposed convolutional neural network architecture reports favorable results, with an overall classification accuracy of 0.6990 for cancer classification and 0.8144 for necrosis detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

List mode multichannel analyzer

DOEpatents

Archer, Daniel E [Livermore, CA; Luke, S John [Pleasanton, CA; Mauger, G Joseph [Livermore, CA; Riot, Vincent J [Berkeley, CA; Knapp, David A [Livermore, CA

2007-08-07

A digital list mode multichannel analyzer (MCA) built around a programmable FPGA device for onboard data analysis and on-the-fly modification of system detection/operating parameters, and capable of collecting and processing data in very small time bins (<1 millisecond) when used in histogramming mode, or in list mode as a list mode MCA.

High frequency measurements of shot noise suppression in atomic-scale metal contacts

NASA Astrophysics Data System (ADS)

Wheeler, Patrick J.; Evans, Kenneth; Russom, Jeffrey; King, Nicholas; Natelson, Douglas

2009-03-01

Shot noise provides a means of assessing the number and transmission coefficients of transmitting channels in atomic- and molecular-scale junctions. Previous experiments at low temperatures in metal and semiconductor point contacts have demonstrated the expected suppression of shot noise when junction conductance is near an integer multiple of the conductance quantum, G0≡2e^2/h. Using high frequency techniques, we demonstrate the high speed acquisition of such data at room temperature in mechanical break junctions. In clean Au contacts conductance histograms with clear peaks at G0, 2G0, and 3G0 are acquired within hours, and histograms of simultaneous measurements of the shot noise show clear suppression at those conductance values. We describe the dependence of the noise on bias voltage and analyze the noise vs. conductance histograms in terms of a model that averages over transmission coefficients.

SEDIDAT: A BASIC program for the collection and statistical analysis of particle settling velocity data

NASA Astrophysics Data System (ADS)

Wright, Robyn; Thornberg, Steven M.

SEDIDAT is a series of compiled IBM-BASIC (version 2.0) programs that direct the collection, statistical calculation, and graphic presentation of particle settling velocity and equivalent spherical diameter for samples analyzed using the settling tube technique. The programs follow a menu-driven format that is understood easily by students and scientists with little previous computer experience. Settling velocity is measured directly (cm,sec) and also converted into Chi units. Equivalent spherical diameter (reported in Phi units) is calculated using a modified Gibbs equation for different particle densities. Input parameters, such as water temperature, settling distance, particle density, run time, and Phi;Chi interval are changed easily at operator discretion. Optional output to a dot-matrix printer includes a summary of moment and graphic statistical parameters, a tabulation of individual and cumulative weight percents, a listing of major distribution modes, and cumulative and histogram plots of a raw time, settling velocity. Chi and Phi data.

Histogram Analysis of CT Perfusion of Hepatocellular Carcinoma for Predicting Response to Transarterial Radioembolization: Value of Tumor Heterogeneity Assessment.

PubMed

Reiner, Caecilia S; Gordic, Sonja; Puippe, Gilbert; Morsbach, Fabian; Wurnig, Moritz; Schaefer, Niklaus; Veit-Haibach, Patrick; Pfammatter, Thomas; Alkadhi, Hatem

2016-03-01

To evaluate in patients with hepatocellular carcinoma (HCC), whether assessment of tumor heterogeneity by histogram analysis of computed tomography (CT) perfusion helps predicting response to transarterial radioembolization (TARE). Sixteen patients (15 male; mean age 65 years; age range 47-80 years) with HCC underwent CT liver perfusion for treatment planning prior to TARE with Yttrium-90 microspheres. Arterial perfusion (AP) derived from CT perfusion was measured in the entire tumor volume, and heterogeneity was analyzed voxel-wise by histogram analysis. Response to TARE was evaluated on follow-up imaging (median follow-up, 129 days) based on modified Response Evaluation Criteria in Solid Tumors (mRECIST). Results of histogram analysis and mean AP values of the tumor were compared between responders and non-responders. Receiver operating characteristics were calculated to determine the parameters' ability to discriminate responders from non-responders. According to mRECIST, 8 patients (50%) were responders and 8 (50%) non-responders. Comparing responders and non-responders, the 50th and 75th percentile of AP derived from histogram analysis was significantly different [AP 43.8/54.3 vs. 27.6/34.3 mL min(-1) 100 mL(-1)); p < 0.05], while the mean AP of HCCs (43.5 vs. 27.9 mL min(-1) 100 mL(-1); p > 0.05) was not. Further heterogeneity parameters from histogram analysis (skewness, coefficient of variation, and 25th percentile) did not differ between responders and non-responders (p > 0.05). If the cut-off for the 75th percentile was set to an AP of 37.5 mL min(-1) 100 mL(-1), therapy response could be predicted with a sensitivity of 88% (7/8) and specificity of 75% (6/8). Voxel-wise histogram analysis of pretreatment CT perfusion indicating tumor heterogeneity of HCC improves the pretreatment prediction of response to TARE.

Histogram Analysis of Diffusion Tensor Imaging Parameters in Pediatric Cerebellar Tumors.

PubMed

Wagner, Matthias W; Narayan, Anand K; Bosemani, Thangamadhan; Huisman, Thierry A G M; Poretti, Andrea

2016-05-01

Apparent diffusion coefficient (ADC) values have been shown to assist in differentiating cerebellar pilocytic astrocytomas and medulloblastomas. Previous studies have applied only ADC measurements and calculated the mean/median values. Here we investigated the value of diffusion tensor imaging (DTI) histogram characteristics of the entire tumor for differentiation of cerebellar pilocytic astrocytomas and medulloblastomas. Presurgical DTI data were analyzed with a region of interest (ROI) approach to include the entire tumor. For each tumor, histogram-derived metrics including the 25th percentile, 75th percentile, and skewness were calculated for fractional anisotropy (FA) and mean (MD), axial (AD), and radial (RD) diffusivity. The histogram metrics were used as primary predictors of interest in a logistic regression model. Statistical significance levels were set at p < .01. The study population included 17 children with pilocytic astrocytoma and 16 with medulloblastoma (mean age, 9.21 ± 5.18 years and 7.66 ± 4.97 years, respectively). Compared to children with medulloblastoma, children with pilocytic astrocytoma showed higher MD (P = .003 and P = .008), AD (P = .004 and P = .007), and RD (P = .003 and P = .009) values for the 25th and 75th percentile. In addition, histogram skewness showed statistically significant differences for MD between low- and high-grade tumors (P = .008). The 25th percentile for MD yields the best results for the presurgical differentiation between pediatric cerebellar pilocytic astrocytomas and medulloblastomas. The analysis of other DTI metrics does not provide additional diagnostic value. Our study confirms the diagnostic value of the quantitative histogram analysis of DTI data in pediatric neuro-oncology. Copyright © 2015 by the American Society of Neuroimaging.

Assessment of Arterial Wall Enhancement for Differentiation of Parent Artery Disease from Small Artery Disease: Comparison between Histogram Analysis and Visual Analysis on 3-Dimensional Contrast-Enhanced T1-Weighted Turbo Spin Echo MR Images at 3T.

PubMed

Jang, Jinhee; Kim, Tae-Won; Hwang, Eo-Jin; Choi, Hyun Seok; Koo, Jaseong; Shin, Yong Sam; Jung, So-Lyung; Ahn, Kook-Jin; Kim, Bum-Soo

2017-01-01

The purpose of this study was to compare the histogram analysis and visual scores in 3T MRI assessment of middle cerebral arterial wall enhancement in patients with acute stroke, for the differentiation of parent artery disease (PAD) from small artery disease (SAD). Among the 82 consecutive patients in a tertiary hospital for one year, 25 patients with acute infarcts in middle cerebral artery (MCA) territory were included in this study including 15 patients with PAD and 10 patients with SAD. Three-dimensional contrast-enhanced T1-weighted turbo spin echo MR images with black-blood preparation at 3T were analyzed both qualitatively and quantitatively. The degree of MCA stenosis, and visual and histogram assessments on MCA wall enhancement were evaluated. A statistical analysis was performed to compare diagnostic accuracy between qualitative and quantitative metrics. The degree of stenosis, visual enhancement score, geometric mean (GM), and the 90th percentile (90P) value from the histogram analysis were significantly higher in PAD than in SAD ( p = 0.006 for stenosis, < 0.001 for others). The receiver operating characteristic curve area of GM and 90P were 1 (95% confidence interval [CI], 0.86-1.00). A histogram analysis of a relevant arterial wall enhancement allows differentiation between PAD and SAD in patients with acute stroke within the MCA territory.

Utility of histogram analysis of apparent diffusion coefficient maps obtained using 3.0T MRI for distinguishing uterine carcinosarcoma from endometrial carcinoma.

PubMed

Takahashi, Masahiro; Kozawa, Eito; Tanisaka, Megumi; Hasegawa, Kousei; Yasuda, Masanori; Sakai, Fumikazu

2016-06-01

We explored the role of histogram analysis of apparent diffusion coefficient (ADC) maps for discriminating uterine carcinosarcoma and endometrial carcinoma. We retrospectively evaluated findings in 13 patients with uterine carcinosarcoma and 50 patients with endometrial carcinoma who underwent diffusion-weighted imaging (b = 0, 500, 1000 s/mm(2) ) at 3T with acquisition of corresponding ADC maps. We derived histogram data from regions of interest drawn on all slices of the ADC maps in which tumor was visualized, excluding areas of necrosis and hemorrhage in the tumor. We used the Mann-Whitney test to evaluate the capacity of histogram parameters (mean ADC value, 5th to 95th percentiles, skewness, kurtosis) to discriminate uterine carcinosarcoma and endometrial carcinoma and analyzed the receiver operating characteristic (ROC) curve to determine the optimum threshold value for each parameter and its corresponding sensitivity and specificity. Carcinosarcomas demonstrated significantly higher mean vales of ADC, 95th, 90th, 75th, 50th, 25th percentiles and kurtosis than endometrial carcinomas (P < 0.05). ROC curve analysis of the 75th percentile yielded the best area under the ROC curve (AUC; 0.904), sensitivity of 100%, and specificity of 78.0%, with a cutoff value of 1.034 × 10(-3) mm(2) /s. Histogram analysis of ADC maps might be helpful for discriminating uterine carcinosarcomas and endometrial carcinomas. J. Magn. Reson. Imaging 2016;43:1301-1307. © 2015 Wiley Periodicals, Inc.

Histogram Analysis of Apparent Diffusion Coefficients for Occult Tonsil Cancer in Patients with Cervical Nodal Metastasis from an Unknown Primary Site at Presentation.

PubMed

Choi, Young Jun; Lee, Jeong Hyun; Kim, Hye Ok; Kim, Dae Yoon; Yoon, Ra Gyoung; Cho, So Hyun; Koh, Myeong Ju; Kim, Namkug; Kim, Sang Yoon; Baek, Jung Hwan

2016-01-01

To explore the added value of histogram analysis of apparent diffusion coefficient (ADC) values over magnetic resonance (MR) imaging and fluorine 18 ((18)F) fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) for the detection of occult palatine tonsil squamous cell carcinoma (SCC) in patients with cervical nodal metastasis from a cancer of an unknown primary site. The institutional review board approved this retrospective study, and the requirement for informed consent was waived. Differences in the bimodal histogram parameters of the ADC values were assessed among occult palatine tonsil SCC (n = 19), overt palatine tonsil SCC (n = 20), and normal palatine tonsils (n = 20). One-way analysis of variance was used to analyze differences among the three groups. Receiver operating characteristic curve analysis was used to determine the best differentiating parameters. The increased sensitivity of histogram analysis over MR imaging and (18)F-FDG PET/CT for the detection of occult palatine tonsil SCC was evaluated as added value. Histogram analysis showed statistically significant differences in the mean, standard deviation, and 50th and 90th percentile ADC values among the three groups (P < .0045). Occult palatine tonsil SCC had a significantly higher standard deviation for the overall curves, mean and standard deviation of the higher curves, and 90th percentile ADC value, compared with normal palatine tonsils (P < .0167). Receiver operating characteristic curve analysis showed that the standard deviation of the overall curve best delineated occult palatine tonsil SCC from normal palatine tonsils, with a sensitivity of 78.9% (15 of 19 patients) and a specificity of 60% (12 of 20 patients). The added value of ADC histogram analysis was 52.6% over MR imaging alone and 15.8% over combined conventional MR imaging and (18)F-FDG PET/CT. Adding ADC histogram analysis to conventional MR imaging can improve the detection sensitivity for occult palatine tonsil SCC in patients with a cervical nodal metastasis originating from a cancer of an unknown primary site. © RSNA, 2015.

Histogram Matching Extends Acceptable Signal Strength Range on Optical Coherence Tomography Images

PubMed Central

Chen, Chieh-Li; Ishikawa, Hiroshi; Wollstein, Gadi; Bilonick, Richard A.; Sigal, Ian A.; Kagemann, Larry; Schuman, Joel S.

2015-01-01

Purpose. We minimized the influence of image quality variability, as measured by signal strength (SS), on optical coherence tomography (OCT) thickness measurements using the histogram matching (HM) method. Methods. We scanned 12 eyes from 12 healthy subjects with the Cirrus HD-OCT device to obtain a series of OCT images with a wide range of SS (maximal range, 1–10) at the same visit. For each eye, the histogram of an image with the highest SS (best image quality) was set as the reference. We applied HM to the images with lower SS by shaping the input histogram into the reference histogram. Retinal nerve fiber layer (RNFL) thickness was automatically measured before and after HM processing (defined as original and HM measurements), and compared to the device output (device measurements). Nonlinear mixed effects models were used to analyze the relationship between RNFL thickness and SS. In addition, the lowest tolerable SSs, which gave the RNFL thickness within the variability margin of manufacturer recommended SS range (6–10), were determined for device, original, and HM measurements. Results. The HM measurements showed less variability across a wide range of image quality than the original and device measurements (slope = 1.17 vs. 4.89 and 1.72 μm/SS, respectively). The lowest tolerable SS was successfully reduced to 4.5 after HM processing. Conclusions. The HM method successfully extended the acceptable SS range on OCT images. This would qualify more OCT images with low SS for clinical assessment, broadening the OCT application to a wider range of subjects. PMID:26066749

Content based Image Retrieval based on Different Global and Local Color Histogram Methods: A Survey

NASA Astrophysics Data System (ADS)

Suhasini, Pallikonda Sarah; Sri Rama Krishna, K.; Murali Krishna, I. V.

2017-02-01

Different global and local color histogram methods for content based image retrieval (CBIR) are investigated in this paper. Color histogram is a widely used descriptor for CBIR. Conventional method of extracting color histogram is global, which misses the spatial content, is less invariant to deformation and viewpoint changes, and results in a very large three dimensional histogram corresponding to the color space used. To address the above deficiencies, different global and local histogram methods are proposed in recent research. Different ways of extracting local histograms to have spatial correspondence, invariant colour histogram to add deformation and viewpoint invariance and fuzzy linking method to reduce the size of the histogram are found in recent papers. The color space and the distance metric used are vital in obtaining color histogram. In this paper the performance of CBIR based on different global and local color histograms in three different color spaces, namely, RGB, HSV, L*a*b* and also with three distance measures Euclidean, Quadratic and Histogram intersection are surveyed, to choose appropriate method for future research.

``Sweetening'' Technical Physics with Hershey's Kisses

NASA Astrophysics Data System (ADS)

Stone, Chuck

2003-04-01

This paper describes an activity in which students measure the mass of each candy in one full bag of Hershey's Kisses and then use a simple spreadsheet program to construct a histogram showing the number of candies as a function of mass. Student measurements indicate that one single bag of 80 Kisses yields enough data to produce a noticeable variation in the candy's mass distribution. The bimodal character of this distribution provides a useful discussion topic. This activity can be performed as a classroom project, a laboratory exercise, or an interactive lecture demonstration. In all these formats, students have the opportunity to collect, organize, process, and analyze real data. In addition to strengthening graphical analysis skills, this activity introduces students to fundamentals of statistics, manufacturing processes in the industrial workplace, and process control techniques.

Naturalness preservation image contrast enhancement via histogram modification

NASA Astrophysics Data System (ADS)

Tian, Qi-Chong; Cohen, Laurent D.

2018-04-01

Contrast enhancement is a technique for enhancing image contrast to obtain better visual quality. Since many existing contrast enhancement algorithms usually produce over-enhanced results, the naturalness preservation is needed to be considered in the framework of image contrast enhancement. This paper proposes a naturalness preservation contrast enhancement method, which adopts the histogram matching to improve the contrast and uses the image quality assessment to automatically select the optimal target histogram. The contrast improvement and the naturalness preservation are both considered in the target histogram, so this method can avoid the over-enhancement problem. In the proposed method, the optimal target histogram is a weighted sum of the original histogram, the uniform histogram, and the Gaussian-shaped histogram. Then the structural metric and the statistical naturalness metric are used to determine the weights of corresponding histograms. At last, the contrast-enhanced image is obtained via matching the optimal target histogram. The experiments demonstrate the proposed method outperforms the compared histogram-based contrast enhancement algorithms.

SPA- STATISTICAL PACKAGE FOR TIME AND FREQUENCY DOMAIN ANALYSIS

NASA Technical Reports Server (NTRS)

Brownlow, J. D.

1994-01-01

The need for statistical analysis often arises when data is in the form of a time series. This type of data is usually a collection of numerical observations made at specified time intervals. Two kinds of analysis may be performed on the data. First, the time series may be treated as a set of independent observations using a time domain analysis to derive the usual statistical properties including the mean, variance, and distribution form. Secondly, the order and time intervals of the observations may be used in a frequency domain analysis to examine the time series for periodicities. In almost all practical applications, the collected data is actually a mixture of the desired signal and a noise signal which is collected over a finite time period with a finite precision. Therefore, any statistical calculations and analyses are actually estimates. The Spectrum Analysis (SPA) program was developed to perform a wide range of statistical estimation functions. SPA can provide the data analyst with a rigorous tool for performing time and frequency domain studies. In a time domain statistical analysis the SPA program will compute the mean variance, standard deviation, mean square, and root mean square. It also lists the data maximum, data minimum, and the number of observations included in the sample. In addition, a histogram of the time domain data is generated, a normal curve is fit to the histogram, and a goodness-of-fit test is performed. These time domain calculations may be performed on both raw and filtered data. For a frequency domain statistical analysis the SPA program computes the power spectrum, cross spectrum, coherence, phase angle, amplitude ratio, and transfer function. The estimates of the frequency domain parameters may be smoothed with the use of Hann-Tukey, Hamming, Barlett, or moving average windows. Various digital filters are available to isolate data frequency components. Frequency components with periods longer than the data collection interval are removed by least-squares detrending. As many as ten channels of data may be analyzed at one time. Both tabular and plotted output may be generated by the SPA program. This program is written in FORTRAN IV and has been implemented on a CDC 6000 series computer with a central memory requirement of approximately 142K (octal) of 60 bit words. This core requirement can be reduced by segmentation of the program. The SPA program was developed in 1978.

METAGUI. A VMD interface for analyzing metadynamics and molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Biarnés, Xevi; Pietrucci, Fabio; Marinelli, Fabrizio; Laio, Alessandro

2012-01-01

We present a new computational tool, METAGUI, which extends the VMD program with a graphical user interface that allows constructing a thermodynamic and kinetic model of a given process simulated by large-scale molecular dynamics. The tool is specially designed for analyzing metadynamics based simulations. The huge amount of diverse structures generated during such a simulation is partitioned into a set of microstates (i.e. structures with similar values of the collective variables). Their relative free energies are then computed by a weighted-histogram procedure and the most relevant free energy wells are identified by diagonalization of the rate matrix followed by a commitor analysis. All this procedure leads to a convenient representation of the metastable states and long-time kinetics of the system which can be compared with experimental data. The tool allows to seamlessly switch between a collective variables space representation of microstates and their atomic structure representation, which greatly facilitates the set-up and analysis of molecular dynamics simulations. METAGUI is based on the output format of the PLUMED plugin, making it compatible with a number of different molecular dynamics packages like AMBER, NAMD, GROMACS and several others. The METAGUI source files can be downloaded from the PLUMED web site ( http://www.plumed-code.org). Program summaryProgram title: METAGUI Catalogue identifier: AEKH_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKH_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License version 3 No. of lines in distributed program, including test data, etc.: 117 545 No. of bytes in distributed program, including test data, etc.: 8 516 203 Distribution format: tar.gz Programming language: TK/TCL, Fortran Computer: Any computer with a VMD installation and capable of running an executable produced by a gfortran compiler Operating system: Linux, Unix OS-es RAM: 1 073 741 824 bytes Classification: 23 External routines: A VMD installation ( http://www.ks.uiuc.edu/Research/vmd/) Nature of problem: Extract thermodynamic data and build a kinetic model of a given process simulated by metadynamics or molecular dynamics simulations, and provide this information on a dual representation that allows navigating and exploring the molecular structures corresponding to each point along the multi-dimensional free energy hypersurface. Solution method: Graphical-user interface linked to VMD that clusterizes the simulation trajectories in the space of a set of collective variables and assigns each frame to a given microstate, determines the free energy of each microstate by a weighted histogram analysis method, and identifies the most relevant free energy wells (kinetic basins) by diagonalization of the rate matrix followed by a commitor analysis. Restrictions: Input format files compatible with PLUMED and all the MD engines supported by PLUMED and VMD. Running time: A few minutes.

LinoSPAD: a time-resolved 256×1 CMOS SPAD line sensor system featuring 64 FPGA-based TDC channels running at up to 8.5 giga-events per second

NASA Astrophysics Data System (ADS)

Burri, Samuel; Homulle, Harald; Bruschini, Claudio; Charbon, Edoardo

2016-04-01

LinoSPAD is a reconfigurable camera sensor with a 256×1 CMOS SPAD (single-photon avalanche diode) pixel array connected to a low cost Xilinx Spartan 6 FPGA. The LinoSPAD sensor's line of pixels has a pitch of 24 μm and 40% fill factor. The FPGA implements an array of 64 TDCs and histogram engines capable of processing up to 8.5 giga-photons per second. The LinoSPAD sensor measures 1.68 mm×6.8 mm and each pixel has a direct digital output to connect to the FPGA. The chip is bonded on a carrier PCB to connect to the FPGA motherboard. 64 carry chain based TDCs sampled at 400 MHz can generate a timestamp every 7.5 ns with a mean time resolution below 25 ps per code. The 64 histogram engines provide time-of-arrival histograms covering up to 50 ns. An alternative mode allows the readout of 28 bit timestamps which have a range of up to 4.5 ms. Since the FPGA TDCs have considerable non-linearity we implemented a correction module capable of increasing histogram linearity at real-time. The TDC array is interfaced to a computer using a super-speed USB3 link to transfer over 150k histograms per second for the 12.5 ns reference period used in our characterization. After characterization and subsequent programming of the post-processing we measure an instrument response histogram shorter than 100 ps FWHM using a strong laser pulse with 50 ps FWHM. A timing resolution that when combined with the high fill factor makes the sensor well suited for a wide variety of applications from fluorescence lifetime microscopy over Raman spectroscopy to 3D time-of-flight.

Isobio software: biological dose distribution and biological dose volume histogram from physical dose conversion using linear-quadratic-linear model.

PubMed

Jaikuna, Tanwiwat; Khadsiri, Phatchareewan; Chawapun, Nisa; Saekho, Suwit; Tharavichitkul, Ekkasit

2017-02-01

To develop an in-house software program that is able to calculate and generate the biological dose distribution and biological dose volume histogram by physical dose conversion using the linear-quadratic-linear (LQL) model. The Isobio software was developed using MATLAB version 2014b to calculate and generate the biological dose distribution and biological dose volume histograms. The physical dose from each voxel in treatment planning was extracted through Computational Environment for Radiotherapy Research (CERR), and the accuracy was verified by the differentiation between the dose volume histogram from CERR and the treatment planning system. An equivalent dose in 2 Gy fraction (EQD 2 ) was calculated using biological effective dose (BED) based on the LQL model. The software calculation and the manual calculation were compared for EQD 2 verification with pair t -test statistical analysis using IBM SPSS Statistics version 22 (64-bit). Two and three-dimensional biological dose distribution and biological dose volume histogram were displayed correctly by the Isobio software. Different physical doses were found between CERR and treatment planning system (TPS) in Oncentra, with 3.33% in high-risk clinical target volume (HR-CTV) determined by D 90% , 0.56% in the bladder, 1.74% in the rectum when determined by D 2cc , and less than 1% in Pinnacle. The difference in the EQD 2 between the software calculation and the manual calculation was not significantly different with 0.00% at p -values 0.820, 0.095, and 0.593 for external beam radiation therapy (EBRT) and 0.240, 0.320, and 0.849 for brachytherapy (BT) in HR-CTV, bladder, and rectum, respectively. The Isobio software is a feasible tool to generate the biological dose distribution and biological dose volume histogram for treatment plan evaluation in both EBRT and BT.

Detection of Abnormal Events via Optical Flow Feature Analysis

PubMed Central

Wang, Tian; Snoussi, Hichem

2015-01-01

In this paper, a novel algorithm is proposed to detect abnormal events in video streams. The algorithm is based on the histogram of the optical flow orientation descriptor and the classification method. The details of the histogram of the optical flow orientation descriptor are illustrated for describing movement information of the global video frame or foreground frame. By combining one-class support vector machine and kernel principal component analysis methods, the abnormal events in the current frame can be detected after a learning period characterizing normal behaviors. The difference abnormal detection results are analyzed and explained. The proposed detection method is tested on benchmark datasets, then the experimental results show the effectiveness of the algorithm. PMID:25811227

A comparison of methods using optical coherence tomography to detect demineralized regions in teeth

PubMed Central

Sowa, Michael G.; Popescu, Dan P.; Friesen, Jeri R.; Hewko, Mark D.; Choo-Smith, Lin-P’ing

2013-01-01

Optical coherence tomography (OCT) is a three- dimensional optical imaging technique that can be used to identify areas of early caries formation in dental enamel. The OCT signal at 850 nm back-reflected from sound enamel is attenuated stronger than the signal back-reflected from demineralized regions. To quantify this observation, the OCT signal as a function of depth into the enamel (also known as the A-scan intensity), the histogram of the A-scan intensities and three summary parameters derived from the A-scan are defined and their diagnostic potential compared. A total of 754 OCT A-scans were analyzed. The three summary parameters derived from the A-scans, the OCT attenuation coefficient as well as the mean and standard deviation of the lognormal fit to the histogram of the A-scan ensemble show statistically significant differences (p < 0.01) when comparing parameters from sound enamel and caries. Furthermore, these parameters only show a modest correlation. Based on the area under the curve (AUC) of the receiver operating characteristics (ROC) plot, the OCT attenuation coefficient shows higher discriminatory capacity (AUC=0.98) compared to the parameters derived from the lognormal fit to the histogram of the A-scan. However, direct analysis of the A-scans or the histogram of A-scan intensities using linear support vector machine classification shows diagnostic discrimination (AUC = 0.96) comparable to that achieved using the attenuation coefficient. These findings suggest that either direct analysis of the A-scan, its intensity histogram or the attenuation coefficient derived from the descending slope of the OCT A-scan have high capacity to discriminate between regions of caries and sound enamel. PMID:22052833

Control system of hexacopter using color histogram footprint and convolutional neural network

NASA Astrophysics Data System (ADS)

Ruliputra, R. N.; Darma, S.

2017-07-01

The development of unmanned aerial vehicles (UAV) has been growing rapidly in recent years. The use of logic thinking which is implemented into the program algorithms is needed to make a smart system. By using visual input from a camera, UAV is able to fly autonomously by detecting a target. However, some weaknesses arose as usage in the outdoor environment might change the target's color intensity. Color histogram footprint overcomes the problem because it divides color intensity into separate bins that make the detection tolerant to the slight change of color intensity. Template matching compare its detection result with a template of the reference image to determine the target position and use it to position the vehicle in the middle of the target with visual feedback control based on Proportional-Integral-Derivative (PID) controller. Color histogram footprint method localizes the target by calculating the back projection of its histogram. It has an average success rate of 77 % from a distance of 1 meter. It can position itself in the middle of the target by using visual feedback control with an average positioning time of 73 seconds. After the hexacopter is in the middle of the target, Convolutional Neural Networks (CNN) classifies a number contained in the target image to determine a task depending on the classified number, either landing, yawing, or return to launch. The recognition result shows an optimum success rate of 99.2 %.

Preprocessing with image denoising and histogram equalization for endoscopy image analysis using texture analysis.

PubMed

Hiroyasu, Tomoyuki; Hayashinuma, Katsutoshi; Ichikawa, Hiroshi; Yagi, Nobuaki

2015-08-01

A preprocessing method for endoscopy image analysis using texture analysis is proposed. In a previous study, we proposed a feature value that combines a co-occurrence matrix and a run-length matrix to analyze the extent of early gastric cancer from images taken with narrow-band imaging endoscopy. However, the obtained feature value does not identify lesion zones correctly due to the influence of noise and halation. Therefore, we propose a new preprocessing method with a non-local means filter for de-noising and contrast limited adaptive histogram equalization. We have confirmed that the pattern of gastric mucosa in images can be improved by the proposed method. Furthermore, the lesion zone is shown more correctly by the obtained color map.

Histogram Analysis of CT Perfusion of Hepatocellular Carcinoma for Predicting Response to Transarterial Radioembolization: Value of Tumor Heterogeneity Assessment

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

Reiner, Caecilia S., E-mail: caecilia.reiner@usz.ch; Gordic, Sonja; Puippe, Gilbert

2016-03-15

PurposeTo evaluate in patients with hepatocellular carcinoma (HCC), whether assessment of tumor heterogeneity by histogram analysis of computed tomography (CT) perfusion helps predicting response to transarterial radioembolization (TARE).Materials and MethodsSixteen patients (15 male; mean age 65 years; age range 47–80 years) with HCC underwent CT liver perfusion for treatment planning prior to TARE with Yttrium-90 microspheres. Arterial perfusion (AP) derived from CT perfusion was measured in the entire tumor volume, and heterogeneity was analyzed voxel-wise by histogram analysis. Response to TARE was evaluated on follow-up imaging (median follow-up, 129 days) based on modified Response Evaluation Criteria in Solid Tumors (mRECIST). Results of histogrammore » analysis and mean AP values of the tumor were compared between responders and non-responders. Receiver operating characteristics were calculated to determine the parameters’ ability to discriminate responders from non-responders.ResultsAccording to mRECIST, 8 patients (50 %) were responders and 8 (50 %) non-responders. Comparing responders and non-responders, the 50th and 75th percentile of AP derived from histogram analysis was significantly different [AP 43.8/54.3 vs. 27.6/34.3 mL min{sup −1} 100 mL{sup −1}); p < 0.05], while the mean AP of HCCs (43.5 vs. 27.9 mL min{sup −1} 100 mL{sup −1}; p > 0.05) was not. Further heterogeneity parameters from histogram analysis (skewness, coefficient of variation, and 25th percentile) did not differ between responders and non-responders (p > 0.05). If the cut-off for the 75th percentile was set to an AP of 37.5 mL min{sup −1} 100 mL{sup −1}, therapy response could be predicted with a sensitivity of 88 % (7/8) and specificity of 75 % (6/8).ConclusionVoxel-wise histogram analysis of pretreatment CT perfusion indicating tumor heterogeneity of HCC improves the pretreatment prediction of response to TARE.« less

The value of whole lesion ADC histogram profiling to differentiate between morphologically indistinguishable ring enhancing lesions-comparison of glioblastomas and brain abscesses.

PubMed

Horvath-Rizea, Diana; Surov, Alexey; Hoffmann, Karl-Titus; Garnov, Nikita; Vörkel, Cathrin; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Bäzner, Hansjörg; Gihr, Georg Alexander; Kalman, Marcell; Henkes, Elina; Henkes, Hans; Schob, Stefan

2018-04-06

Morphologically similar appearing ring enhancing lesions in the brain parenchyma can be caused by a number of distinct pathologies, however, they consistently represent life-threatening conditions. The two most frequently encountered diseases manifesting as such are glioblastoma multiforme (GBM) and brain abscess (BA), each requiring disparate therapeutical approaches. As a result of their morphological resemblance, essential treatment might be significantly delayed or even ommited, in case results of conventional imaging remain inconclusive. Therefore, our study aimed to investigate, whether ADC histogram profiling reliably can distinguish between both entities, thus enhancing the differential diagnostic process and preventing treatment failure in this highly critical context. 103 patients (51 BA, 52 GBM) with histopathologically confirmed diagnosis were enrolled. Pretreatment diffusion weighted imaging (DWI) was obtained in a 1.5T system using b values of 0, 500, and 1000 s/mm 2 . Whole lesion ADC volumes were analyzed using a histogram-based approach. Statistical analysis was performed using SPSS version 23. All investigated parameters were statistically different in comparison of both groups. Most importantly, ADCp10 was able to differentiate reliably between BA and GBM with excellent accuracy (0.948) using a cutpoint value of 70 × 10 -5 mm 2 × s -1 . ADC whole lesion histogram profiling provides a valuable tool to differentiate between morphologically indistinguishable mass lesions. Among the investigated parameters, the 10th percentile of the ADC volume distinguished best between GBM and BA.

Detection of white spot lesions by segmenting laser speckle images using computer vision methods.

PubMed

Gavinho, Luciano G; Araujo, Sidnei A; Bussadori, Sandra K; Silva, João V P; Deana, Alessandro M

2018-05-05

This paper aims to develop a method for laser speckle image segmentation of tooth surfaces for diagnosis of early stages caries. The method, applied directly to a raw image obtained by digital photography, is based on the difference between the speckle pattern of a carious lesion tooth surface area and that of a sound area. Each image is divided into blocks which are identified in a working matrix by their χ 2 distance between block histograms of the analyzed image and the reference histograms previously obtained by K-means from healthy (h_Sound) and lesioned (h_Decay) areas, separately. If the χ 2 distance between a block histogram and h_Sound is greater than the distance to h_Decay, this block is marked as decayed. The experiments showed that the method can provide effective segmentation for initial lesions. We used 64 images to test the algorithm and we achieved 100% accuracy in segmentation. Differences between the speckle pattern of a sound tooth surface region and a carious region, even in the early stage, can be evidenced by the χ 2 distance between histograms. This method proves to be more effective for segmenting the laser speckle image, which enhances the contrast between sound and lesioned tissues. The results were obtained with low computational cost. The method has the potential for early diagnosis in a clinical environment, through the development of low-cost portable equipment.

Using Statistical Process Control to Make Data-Based Clinical Decisions.

ERIC Educational Resources Information Center

Pfadt, Al; Wheeler, Donald J.

1995-01-01

Statistical process control (SPC), which employs simple statistical tools and problem-solving techniques such as histograms, control charts, flow charts, and Pareto charts to implement continual product improvement procedures, can be incorporated into human service organizations. Examples illustrate use of SPC procedures to analyze behavioral data…

Computerized image analysis: estimation of breast density on mammograms

NASA Astrophysics Data System (ADS)

Zhou, Chuan; Chan, Heang-Ping; Petrick, Nicholas; Sahiner, Berkman; Helvie, Mark A.; Roubidoux, Marilyn A.; Hadjiiski, Lubomir M.; Goodsitt, Mitchell M.

2000-06-01

An automated image analysis tool is being developed for estimation of mammographic breast density, which may be useful for risk estimation or for monitoring breast density change in a prevention or intervention program. A mammogram is digitized using a laser scanner and the resolution is reduced to a pixel size of 0.8 mm X 0.8 mm. Breast density analysis is performed in three stages. First, the breast region is segmented from the surrounding background by an automated breast boundary-tracking algorithm. Second, an adaptive dynamic range compression technique is applied to the breast image to reduce the range of the gray level distribution in the low frequency background and to enhance the differences in the characteristic features of the gray level histogram for breasts of different densities. Third, rule-based classification is used to classify the breast images into several classes according to the characteristic features of their gray level histogram. For each image, a gray level threshold is automatically determined to segment the dense tissue from the breast region. The area of segmented dense tissue as a percentage of the breast area is then estimated. In this preliminary study, we analyzed the interobserver variation of breast density estimation by two experienced radiologists using BI-RADS lexicon. The radiologists' visually estimated percent breast densities were compared with the computer's calculation. The results demonstrate the feasibility of estimating mammographic breast density using computer vision techniques and its potential to improve the accuracy and reproducibility in comparison with the subjective visual assessment by radiologists.

SICONID: a FORTRAN-77 program for conditional simulation in one dimension

NASA Astrophysics Data System (ADS)

Pardo-Igúzquiza, E.; Chica-Olmo, M.; Delgado-García, J.

1992-07-01

The SICONID program, written in FORTRAN 77 for the conditional simulation of geological variables in one dimension, is presented. The program permits all the necessary steps to obtain a simulated series of the experimental data to be carried out. These states are: acquisition of the experimental values, modelization of the anamorphosis function, variogram of the normal scores, conditional simulation, and restoration of the experimental histogram. A practical case of simulation of the evolution of the groundwater level in a survey to show the operation of the program is given.

As-built design specification for PARHIS

NASA Technical Reports Server (NTRS)

Tompkins, M. A. (Principal Investigator)

1981-01-01

The program is part of the CLASFYG package. It produces histograms of the greeness profile derived parameters alpha, beta, t sub o, and chi squared, which are computed by the CLASFYG program. Alpha is the approximate greeness rise time, beta is the approximate greeness decay time, t sub o is the spectral crop emergence date, and chi squared per degree of freedom is the goodness of fit of the actual data to the computed greeness profile. The program also produces statistical information concerning the parameters.

MRI histogram analysis enables objective and continuous classification of intervertebral disc degeneration.

PubMed

Waldenberg, Christian; Hebelka, Hanna; Brisby, Helena; Lagerstrand, Kerstin Magdalena

2018-05-01

Magnetic resonance imaging (MRI) is the best diagnostic imaging method for low back pain. However, the technique is currently not utilized in its full capacity, often failing to depict painful intervertebral discs (IVDs), potentially due to the rough degeneration classification system used clinically today. MR image histograms, which reflect the IVD heterogeneity, may offer sensitive imaging biomarkers for IVD degeneration classification. This study investigates the feasibility of using histogram analysis as means of objective and continuous grading of IVD degeneration. Forty-nine IVDs in ten low back pain patients (six males, 25-69 years) were examined with MRI (T2-weighted images and T2-maps). Each IVD was semi-automatically segmented on three mid-sagittal slices. Histogram features of the IVD were extracted from the defined regions of interest and correlated to Pfirrmann grade. Both T2-weighted images and T2-maps displayed similar histogram features. Histograms of well-hydrated IVDs displayed two separate peaks, representing annulus fibrosus and nucleus pulposus. Degenerated IVDs displayed decreased peak separation, where the separation was shown to correlate strongly with Pfirrmann grade (P < 0.05). In addition, some degenerated IVDs within the same Pfirrmann grade displayed diametrically different histogram appearances. Histogram features correlated well with IVD degeneration, suggesting that IVD histogram analysis is a suitable tool for objective and continuous IVD degeneration classification. As histogram analysis revealed IVD heterogeneity, it may be a clinical tool for characterization of regional IVD degeneration effects. To elucidate the usefulness of histogram analysis in patient management, IVD histogram features between asymptomatic and symptomatic individuals needs to be compared.

MCNP Output Data Analysis with ROOT (MODAR)

NASA Astrophysics Data System (ADS)

Carasco, C.

2010-06-01

MCNP Output Data Analysis with ROOT (MODAR) is a tool based on CERN's ROOT software. MODAR has been designed to handle time-energy data issued by MCNP simulations of neutron inspection devices using the associated particle technique. MODAR exploits ROOT's Graphical User Interface and functionalities to visualize and process MCNP simulation results in a fast and user-friendly way. MODAR allows to take into account the detection system time resolution (which is not possible with MCNP) as well as detectors energy response function and counting statistics in a straightforward way. Program summaryProgram title: MODAR Catalogue identifier: AEGA_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGA_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 155 373 No. of bytes in distributed program, including test data, etc.: 14 815 461 Distribution format: tar.gz Programming language: C++ Computer: Most Unix workstations and PC Operating system: Most Unix systems, Linux and windows, provided the ROOT package has been installed. Examples where tested under Suse Linux and Windows XP. RAM: Depends on the size of the MCNP output file. The example presented in the article, which involves three two-dimensional 139×740 bins histograms, allocates about 60 MB. These data are running under ROOT and include consumption by ROOT itself. Classification: 17.6 External routines: ROOT version 5.24.00 ( http://root.cern.ch/drupal/) Nature of problem: The output of an MCNP simulation is an ASCII file. The data processing is usually performed by copying and pasting the relevant parts of the ASCII file into Microsoft Excel. Such an approach is satisfactory when the quantity of data is small but is not efficient when the size of the simulated data is large, for example when time-energy correlations are studied in detail such as in problems involving the associated particle technique. In addition, since the finite time resolution of the simulated detector cannot be modeled with MCNP, systems in which time-energy correlation is crucial cannot be described in a satisfactory way. Finally, realistic particle energy deposit in detectors is calculated with MCNP in a two-step process involving type-5 then type-8 tallies. In the first step, the photon flux energy spectrum associated to a time region is selected and serves as a source energy distribution for the second step. Thus, several files must be manipulated before getting the result, which can be time consuming if one needs to study several time regions or different detectors performances. In the same way, modeling counting statistics obtained in a limited acquisition time requires several steps and can also be time consuming. Solution method: In order to overcome the previous limitations, the MODAR C++ code has been written to make use of CERN's ROOT data analysis software. MCNP output data are read from the MCNP output file with dedicated routines. Two-dimensional histograms are filled and can be handled efficiently within the ROOT framework. To keep a user friendly analysis tool, all processing and data display can be done by means of ROOT Graphical User Interface. Specific routines have been written to include detectors finite time resolution and energy response function as well as counting statistics in a straightforward way. Additional comments: The possibility of adding tallies has also been incorporated in MODAR in order to describe systems in which the signal from several detectors can be summed. Moreover, MODAR can be adapted to handle other problems involving two-dimensional data. Running time: The CPU time needed to smear a two-dimensional histogram depends on the size of the histogram. In the presented example, the time-energy smearing of one of the 139×740 two-dimensional histograms takes 3 minutes with a DELL computer equipped with INTEL Core 2.

Web servlet-assisted, dial-in flow cytometry data analysis.

PubMed

Battye, F

2001-02-01

The obvious benefits of centralized data storage notwithstanding, the size of modern flow cytometry data files discourages their transmission over commonly used telephone modem connections. The proposed solution is to install at the central location a web servlet that can extract compact data arrays, of a form dependent on the requested display type, from the stored files and transmit them to a remote client computer program for display. A client program and a web servlet, both written in the Java programming language, were designed to communicate over standard network connections. The client program creates familiar numerical and graphical display types and allows the creation of gates from combinations of user-defined regions. Data compression techniques further reduce transmission times for data arrays that are already much smaller than the data file itself. For typical data files, network transmission times were reduced more than 700-fold for extraction of one-dimensional (1-D) histograms, between 18 and 120-fold for 2-D histograms, and 6-fold for color-coded dot plots. Numerous display formats are possible without further access to the data file. This scheme enables telephone modem access to centrally stored data without restricting flexibility of display format or preventing comparisons with locally stored files. Copyright 2001 Wiley-Liss, Inc.

Histogram analysis of stretched-exponential and monoexponential diffusion-weighted imaging models for distinguishing low and intermediate/high gleason scores in prostate carcinoma.

PubMed

Liu, Wei; Liu, Xiao H; Tang, Wei; Gao, Hong B; Zhou, Bing N; Zhou, Liang P

2018-02-07

Noninvasive measures to evaluate the aggressiveness of prostate carcinoma (PCa) may benefit patients. To assess the value of stretched-exponential and monoexponential diffusion-weighted imaging (DWI) for predicting the aggressiveness of PCa. Retrospective study. Seventy-five patients with PCa. 3T DWI examinations were performed using b-values of 0, 500, 1000, and 2000 s/mm 2 . The research were based on entire-tumor histogram analysis and the reference standard was radical prostectomy. The correlation analysis was programmed with Spearman's rank-order analysis between the histogram variables and Gleason grade group (GG). Receiver operating characteristic (ROC) regression was used to analyze the ability of these histogram variables to differentiate low-grade (LG) from intermediate/high-grade (HG) PCa. The percentiles and mean of apparent diffusion coefficient (ADC) and distributed diffusion coefficient (DDC) were correlated with GG (ρ: 0.414-0.593), while there was no significant relation among α value, skewnesses, and kurtosises with GG (ρ:0.034-0.323). HG tumors (ADC:484 ± 136, 592 ± 139, 670 ± 144, 788 ± 146, 895 ± 141 mm 2 /s; DDC: 410 ± 142, 532 ± 172, 666 ± 193, 786 ± 196, 914 ± 181 mm 2 /s) had lower values in the 10 th , 25 th , 50 th , 75 th percentiles and means than LG tumors (ADC: 644 ± 779, 737 ± 84, 836 ± 83, 919 ± 82, 997 ± 107 mm 2 /s; DDC: 552 ± 82, 680 ± 94, 829 ± 112, 931 ± 106, 1045 ± 100 mm 2 /s). However, there was no difference between LG and HG tumors in α value (0.671 ± 0.041 vs. 0.633 ± 0.114), kurtosises (ADC 0.09 vs. 0.086; DDC -0.033 vs. -0.317), or skewnesses (ADC -0.036 vs. 0.073; DDC -0.063 vs. 0.136). The above statistics were P < 0.01. ADC10 with AUC = 0.840 and DDC10 with AUC = 0.799 were similar in discriminating between LG and HG PCa at P < 0.05. Histogram variables of DDC and ADC may predict the aggressiveness of PCa, while α value does not. The abilities of ADC10 and DDC10 to discriminate LG from HG tumors were similar, and both better than their respective means. 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Bin Ratio-Based Histogram Distances and Their Application to Image Classification.

PubMed

Hu, Weiming; Xie, Nianhua; Hu, Ruiguang; Ling, Haibin; Chen, Qiang; Yan, Shuicheng; Maybank, Stephen

2014-12-01

Large variations in image background may cause partial matching and normalization problems for histogram-based representations, i.e., the histograms of the same category may have bins which are significantly different, and normalization may produce large changes in the differences between corresponding bins. In this paper, we deal with this problem by using the ratios between bin values of histograms, rather than bin values' differences which are used in the traditional histogram distances. We propose a bin ratio-based histogram distance (BRD), which is an intra-cross-bin distance, in contrast with previous bin-to-bin distances and cross-bin distances. The BRD is robust to partial matching and histogram normalization, and captures correlations between bins with only a linear computational complexity. We combine the BRD with the ℓ1 histogram distance and the χ(2) histogram distance to generate the ℓ1 BRD and the χ(2) BRD, respectively. These combinations exploit and benefit from the robustness of the BRD under partial matching and the robustness of the ℓ1 and χ(2) distances to small noise. We propose a method for assessing the robustness of histogram distances to partial matching. The BRDs and logistic regression-based histogram fusion are applied to image classification. The experimental results on synthetic data sets show the robustness of the BRDs to partial matching, and the experiments on seven benchmark data sets demonstrate promising results of the BRDs for image classification.

Computer-assisted analysis of the vascular endothelial cell motile response to injury.

PubMed

Askey, D B; Herman, I M

1988-12-01

We have developed an automated, user-friendly method to track vascular endothelial cell migration in vitro using an IBM PC/XT with MS DOS. Analog phase-contrast images of the bovine aortic endothelial cells are converted into digital images (8 bit, 250 x 240 pixel resolution) using a Tecmar Video VanGogh A/D board. Digitized images are stored at selected time points following mechanical injury in vitro. FORTRAN and assembly language subroutines have been implemented to automatically detect the wound edge and the edge of each cell nucleus in the phase-contrast, light-microscope field. Detection of the wound edge is accomplished by intensity thresholding following noise reduction in the image and subsequent sampling of the wound. After the range of wound intensities is determined, the entire image is sampled and a histogram of intensities is formed. The histogram peak corresponding to the wound intensities is subtracted, leaving a histogram peak that gives the range of intensities corresponding to the cell nuclei. Rates of cell migration, as well as cellular trajectories and cell surface areas, can be automatically quantitated and analyzed. This inexpensive, automated cell-tracking system should be widely applicable in a variety of cell biologic applications.

Digital image improvement by adding noise: an example by a professional photographer

NASA Astrophysics Data System (ADS)

Kurihara, Takehito; Manabe, Yoshitsugu; Aoki, Naokazu; Kobayashi, Hiroyuki

2008-01-01

To overcome shortcomings of digital image, or to reproduce grain of traditional silver halide photographs, some photographers add noise (grain) to digital image. In an effort to find a factor of preferable noise, we analyzed how a professional photographer introduces noise into B&W digital images and found two noticeable characteristics: 1) there is more noise in mid-tones, gradually decreasing in highlights and shadows toward the ends of tonal range, and 2) histograms in highlights are skewed toward shadows and vice versa, while almost symmetrical in mid-tones. Next, we examined whether the professional's noise could be reproduced. The symmetrical histograms were approximated by Gaussian distribution and skewed ones by chi-square distribution. The images on which the noise was reproduced were judged by the professional himself to be satisfactory enough. As the professional said he added the noise so that "it looked like the grain of B&W gelatin silver photographs," we compared the two kinds of noise and found they have in common: 1) more noise in mid-tones but almost none in brightest highlights and deepest shadows, and 2) asymmetrical histograms in highlights and shadows. We think these common characteristics might be one condition for "good" noise.

Wildfire Detection using by Multi Dimensional Histogram in Boreal Forest

NASA Astrophysics Data System (ADS)

Honda, K.; Kimura, K.; Honma, T.

2008-12-01

Early detection of wildfires is an issue for reduction of damage to environment and human. There are some attempts to detect wildfires by using satellite imagery, which are mainly classified into three methods: Dozier Method(1981-), Threshold Method(1986-) and Contextual Method(1994-). However, the accuracy of these methods is not enough: some commission and omission errors are included in the detected results. In addition, it is not so easy to analyze satellite imagery with high accuracy because of insufficient ground truth data. Kudoh and Hosoi (2003) developed the detection method by using three-dimensional (3D) histogram from past fire data with the NOAA-AVHRR imagery. But their method is impractical because their method depends on their handworks to pick up past fire data from huge data. Therefore, the purpose of this study is to collect fire points as hot spots efficiently from satellite imagery and to improve the method to detect wildfires with the collected data. As our method, we collect past fire data with the Alaska Fire History data obtained by the Alaska Fire Service (AFS). We select points that are expected to be wildfires, and pick up the points inside the fire area of the AFS data. Next, we make 3D histogram with the past fire data. In this study, we use Bands 1, 21 and 32 of MODIS. We calculate the likelihood to detect wildfires with the three-dimensional histogram. As our result, we select wildfires with the 3D histogram effectively. We can detect the troidally spreading wildfire. This result shows the evidence of good wildfire detection. However, the area surrounding glacier tends to rise brightness temperature. It is a false alarm. Burnt area and bare ground are sometimes indicated as false alarms, so that it is necessary to improve this method. Additionally, we are trying various combinations of MODIS bands as the better method to detect wildfire effectively. So as to adjust our method in another area, we are applying our method to tropical forest in Kalimantan, Indonesia and around Chiang Mai, Thailand. But the ground truth data in these areas is lesser than the one in Alaska. Our method needs lots of accurate observed data to make multi-dimensional histogram in the same area. In this study, we can show the system to select wildfire data efficiently from satellite imagery. Furthermore, the development of multi-dimensional histogram from past fire data makes it possible to detect wildfires accurately.

Benchmarking the Degree of Implementation of Learner-Centered Approaches

ERIC Educational Resources Information Center

Blumberg, Phyllis; Pontiggia, Laura

2011-01-01

We describe an objective way to measure whether curricula, educational programs, and institutions are learner-centered. This technique for benchmarking learner-centeredness uses rubrics to measure courses on 29 components within Weimer's five dimensions. We converted the scores on the rubrics to four-point indices and constructed histograms that…

Biogeochemistry of aragonite mud and oolites.

NASA Technical Reports Server (NTRS)

Mitterer, R. M.

1972-01-01

Amino acids were determined on an analyzer similar to that described by Hare (1969) in carbonate mud samples from locations in the Bahamas, Bermuda, Persian Gulf, and Florida Bay, and in oolites from the Gulf of Suez, the Abu Dhabi coast, the Bahamas, and Baffin Bay, Texas. A histogram, tables, and chromatograms of the results are given.

Theory and Application of DNA Histogram Analysis.

ERIC Educational Resources Information Center

Bagwell, Charles Bruce

The underlying principles and assumptions associated with DNA histograms are discussed along with the characteristics of fluorescent probes. Information theory was described and used to calculate the information content of a DNA histogram. Two major types of DNA histogram analyses are proposed: parametric and nonparametric analysis. Three levels…

[Health for All-Italia: an indicator system on health].

PubMed

Burgio, Alessandra; Crialesi, Roberta; Loghi, Marzia

2003-01-01

The Health for All - Italia information system collects health data from several sources. It is intended to be a cornerstone for the achievement of an overview about health in Italy. Health is analyzed at different levels, ranging from health services, health needs, lifestyles, demographic, social, economic and environmental contexts. The database associated software allows to pin down statistical data into graphs and tables, and to carry out simple statistical analysis. It is therefore possible to view the indicators' time series, make simple projections and compare the various indicators over the years for each territorial unit. This is possible by means of tables, graphs (histograms, line graphs, frequencies, linear regression with calculation of correlation coefficients, etc) and maps. These charts can be exported to other programs (i.e. Word, Excel, Power Point), or they can be directly printed in color or black and white.

The value of whole lesion ADC histogram profiling to differentiate between morphologically indistinguishable ring enhancing lesions–comparison of glioblastomas and brain abscesses

PubMed Central

Hoffmann, Karl-Titus; Garnov, Nikita; Vörkel, Cathrin; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Bäzner, Hansjörg; Gihr, Georg Alexander; Kalman, Marcell; Henkes, Elina; Henkes, Hans; Schob, Stefan

2018-01-01

Background Morphologically similar appearing ring enhancing lesions in the brain parenchyma can be caused by a number of distinct pathologies, however, they consistently represent life-threatening conditions. The two most frequently encountered diseases manifesting as such are glioblastoma multiforme (GBM) and brain abscess (BA), each requiring disparate therapeutical approaches. As a result of their morphological resemblance, essential treatment might be significantly delayed or even ommited, in case results of conventional imaging remain inconclusive. Therefore, our study aimed to investigate, whether ADC histogram profiling reliably can distinguish between both entities, thus enhancing the differential diagnostic process and preventing treatment failure in this highly critical context. Methods 103 patients (51 BA, 52 GBM) with histopathologically confirmed diagnosis were enrolled. Pretreatment diffusion weighted imaging (DWI) was obtained in a 1.5T system using b values of 0, 500, and 1000 s/mm2. Whole lesion ADC volumes were analyzed using a histogram-based approach. Statistical analysis was performed using SPSS version 23. Results All investigated parameters were statistically different in comparison of both groups. Most importantly, ADCp10 was able to differentiate reliably between BA and GBM with excellent accuracy (0.948) using a cutpoint value of 70 × 10−5 mm2 × s−1. Conclusions ADC whole lesion histogram profiling provides a valuable tool to differentiate between morphologically indistinguishable mass lesions. Among the investigated parameters, the 10th percentile of the ADC volume distinguished best between GBM and BA. PMID:29719596

Semi-automated camera trap image processing for the detection of ungulate fence crossing events.

PubMed

Janzen, Michael; Visser, Kaitlyn; Visscher, Darcy; MacLeod, Ian; Vujnovic, Dragomir; Vujnovic, Ksenija

2017-09-27

Remote cameras are an increasingly important tool for ecological research. While remote camera traps collect field data with minimal human attention, the images they collect require post-processing and characterization before it can be ecologically and statistically analyzed, requiring the input of substantial time and money from researchers. The need for post-processing is due, in part, to a high incidence of non-target images. We developed a stand-alone semi-automated computer program to aid in image processing, categorization, and data reduction by employing background subtraction and histogram rules. Unlike previous work that uses video as input, our program uses still camera trap images. The program was developed for an ungulate fence crossing project and tested against an image dataset which had been previously processed by a human operator. Our program placed images into categories representing the confidence of a particular sequence of images containing a fence crossing event. This resulted in a reduction of 54.8% of images that required further human operator characterization while retaining 72.6% of the known fence crossing events. This program can provide researchers using remote camera data the ability to reduce the time and cost required for image post-processing and characterization. Further, we discuss how this procedure might be generalized to situations not specifically related to animal use of linear features.

Digital tape unit test facility software

NASA Technical Reports Server (NTRS)

Jackson, J. T.

1971-01-01

Two computer programs are described which are used for the collection and analysis of data from the digital tape unit test facility (DTUTF). The data are the recorded results of skew tests made on magnetic digital tapes which are used on computers as input/output media. The results of each tape test are keypunched onto an 80 column computer card. The format of the card is checked and the card image is stored on a master summary tape via the DTUTF card checking and tape updating system. The master summary tape containing the results of all the tape tests is then used for analysis as input to the DTUTF histogram generating system which produces a histogram of skew vs. date for selected data, followed by some statistical analysis of the data.

Histogram deconvolution - An aid to automated classifiers

NASA Technical Reports Server (NTRS)

Lorre, J. J.

1983-01-01

It is shown that N-dimensional histograms are convolved by the addition of noise in the picture domain. Three methods are described which provide the ability to deconvolve such noise-affected histograms. The purpose of the deconvolution is to provide automated classifiers with a higher quality N-dimensional histogram from which to obtain classification statistics.

Parameterization of the Age-Dependent Whole Brain Apparent Diffusion Coefficient Histogram

PubMed Central

Batra, Marion; Nägele, Thomas

2015-01-01

Purpose. The distribution of apparent diffusion coefficient (ADC) values in the brain can be used to characterize age effects and pathological changes of the brain tissue. The aim of this study was the parameterization of the whole brain ADC histogram by an advanced model with influence of age considered. Methods. Whole brain ADC histograms were calculated for all data and for seven age groups between 10 and 80 years. Modeling of the histograms was performed for two parts of the histogram separately: the brain tissue part was modeled by two Gaussian curves, while the remaining part was fitted by the sum of a Gaussian curve, a biexponential decay, and a straight line. Results. A consistent fitting of the histograms of all age groups was possible with the proposed model. Conclusions. This study confirms the strong dependence of the whole brain ADC histograms on the age of the examined subjects. The proposed model can be used to characterize changes of the whole brain ADC histogram in certain diseases under consideration of age effects. PMID:26609526

Comparison of Histograms for Use in Cloud Observation and Modeling

NASA Technical Reports Server (NTRS)

Green, Lisa; Xu, Kuan-Man

2005-01-01

Cloud observation and cloud modeling data can be presented in histograms for each characteristic to be measured. Combining information from single-cloud histograms yields a summary histogram. Summary histograms can be compared to each other to reach conclusions about the behavior of an ensemble of clouds in different places at different times or about the accuracy of a particular cloud model. As in any scientific comparison, it is necessary to decide whether any apparent differences are statistically significant. The usual methods of deciding statistical significance when comparing histograms do not apply in this case because they assume independent data. Thus, a new method is necessary. The proposed method uses the Euclidean distance metric and bootstrapping to calculate the significance level.

Galvanic Synthesis of Hollow Gold Nanoshells

DTIC Science & Technology

2015-02-01

HAuNS of select diameter and shell thickness were synthesized and tunability of the extinction coefficient was demonstrated through control of the... extinction peak HAuNS ......................................................................................................... 4 Fig. 2 Histogram of...was supported in part by an appointment to the Research Participation Program at the US Army Research Laboratory (ARL) administered by the Oak Ridge

Aromaticity of benzene derivatives: an exploration of the Cambridge Structural Database.

PubMed

Majerz, Irena; Dziembowska, Teresa

2018-04-01

The harmonic oscillator model of aromaticity (HOMA) index, one of the most popular aromaticity indices for solid-state benzene rings in the Cambridge Structural Database (CSD), has been analyzed. The histograms of HOMA for benzene, for benzene derivatives with one formyl, nitro, amino or hydroxy group as well as the histograms for the derivatives with two formyl, nitro, amino or hydroxy groups in ortho, meta and para positions were investigated. The majority of the substituted benzene derivatives in the CSD are characterized by a high value of HOMA, indicating fully aromatic character; however, the distribution of the HOMA value from 1 to about 0 indicates decreasing aromaticity down to non-aromatic character. Among the benzene derivatives investigated, a significant decrease in aromaticity can be related to compounds with diamino and dinitro groups in the meta position.

Computerized system for assessing heart rate variability.

PubMed

Frigy, A; Incze, A; Brânzaniuc, E; Cotoi, S

1996-01-01

The principal theoretical, methodological and clinical aspects of heart rate variability (HRV) analysis are reviewed. This method has been developed over the last 10 years as a useful noninvasive method of measuring the activity of the autonomic nervous system. The main components and the functioning of the computerized rhythm-analyzer system developed by our team are presented. The system is able to perform short-term (maximum 20 minutes) time domain HRV analysis and statistical analysis of the ventricular rate in any rhythm, particularly in atrial fibrillation. The performances of our system are demonstrated by using the graphics (RR histograms, delta RR histograms, RR scattergrams) and the statistical parameters resulted from the processing of three ECG recordings. These recordings are obtained from a normal subject, from a patient with advanced heart failure, and from a patient with atrial fibrillation.

Developing operation algorithms for vision subsystems in autonomous mobile robots

NASA Astrophysics Data System (ADS)

Shikhman, M. V.; Shidlovskiy, S. V.

2018-05-01

The paper analyzes algorithms for selecting keypoints on the image for the subsequent automatic detection of people and obstacles. The algorithm is based on the histogram of oriented gradients and the support vector method. The combination of these methods allows successful selection of dynamic and static objects. The algorithm can be applied in various autonomous mobile robots.

Statistical analysis of landing contact conditions for three lifting body research vehicles

NASA Technical Reports Server (NTRS)

Larson, R. R.

1972-01-01

The landing contact conditions for the HL-10, M2-F2/F3, and the X-24A lifting body vehicles are analyzed statistically for 81 landings. The landing contact parameters analyzed are true airspeed, peak normal acceleration at the center of gravity, roll angle, and roll velocity. Ground measurement parameters analyzed are lateral and longitudinal distance from intended touchdown, lateral distance from touchdown to full stop, and rollout distance. The results are presented in the form of histograms for frequency distributions and cumulative frequency distribution probability curves with a Pearson Type 3 curve fit for extrapolation purposes.

Histogram analysis of T2*-based pharmacokinetic imaging in cerebral glioma grading.

PubMed

Liu, Hua-Shan; Chiang, Shih-Wei; Chung, Hsiao-Wen; Tsai, Ping-Huei; Hsu, Fei-Ting; Cho, Nai-Yu; Wang, Chao-Ying; Chou, Ming-Chung; Chen, Cheng-Yu

2018-03-01

To investigate the feasibility of histogram analysis of the T2*-based permeability parameter volume transfer constant (K trans ) for glioma grading and to explore the diagnostic performance of the histogram analysis of K trans and blood plasma volume (v p ). We recruited 31 and 11 patients with high- and low-grade gliomas, respectively. The histogram parameters of K trans and v p , derived from the first-pass pharmacokinetic modeling based on the T2* dynamic susceptibility-weighted contrast-enhanced perfusion-weighted magnetic resonance imaging (T2* DSC-PW-MRI) from the entire tumor volume, were evaluated for differentiating glioma grades. Histogram parameters of K trans and v p showed significant differences between high- and low-grade gliomas and exhibited significant correlations with tumor grades. The mean K trans derived from the T2* DSC-PW-MRI had the highest sensitivity and specificity for differentiating high-grade gliomas from low-grade gliomas compared with other histogram parameters of K trans and v p . Histogram analysis of T2*-based pharmacokinetic imaging is useful for cerebral glioma grading. The histogram parameters of the entire tumor K trans measurement can provide increased accuracy with additional information regarding microvascular permeability changes for identifying high-grade brain tumors. Copyright © 2017 Elsevier B.V. All rights reserved.

Teaching the Assessment of Normality Using Large Easily-Generated Real Data Sets

ERIC Educational Resources Information Center

Kulp, Christopher W.; Sprechini, Gene D.

2016-01-01

A classroom activity is presented, which can be used in teaching students statistics with an easily generated, large, real world data set. The activity consists of analyzing a video recording of an object. The colour data of the recorded object can then be used as a data set to explore variation in the data using graphs including histograms,…

Probing size-dependent electrokinetics of hematite aggregates

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

Kedra-Królik, Karolina; Rosso, Kevin M.; Zarzycki, Piotr

Aqueous particle suspensions of many kinds are stabilized by the electrostatic potential developed at their surfaces from reaction with water and ions. An important and less well understood aspect of this stabilization is the dependence of the electrostatic surface potential on particle size. Surface electrostatics are typically probed by measuring particle electrophoretic mobilities and quantified in the electrokinetic potential (f), using commercially available Zeta Potential Analyzers (ZPA). Even though ZPAs provide frequency-spectra (histograms) of electrophoretic mobility and hydrodynamic diameter, typically only the maximal-intensity values are reported, despite the information in the remainder of the spectra. Here we propose a mappingmore » procedure that inter-correlates these histograms to extract additional insight, in this case to probe particle size-dependent electrokinetics. Our method is illustrated for a suspension of prototypical iron (III) oxide (hematite, a-Fe2O3). We found that the electrophoretic mobility and f-potential are a linear function of the aggregate size. By analyzing the distribution of surface site types as a function of aggregate size we show that site coordination increases with increasing aggregate diameter. This observation explains why the acidity of the iron oxide particles decreases with increasing particle size.« less

Information granules in image histogram analysis.

PubMed

Wieclawek, Wojciech

2018-04-01

A concept of granular computing employed in intensity-based image enhancement is discussed. First, a weighted granular computing idea is introduced. Then, the implementation of this term in the image processing area is presented. Finally, multidimensional granular histogram analysis is introduced. The proposed approach is dedicated to digital images, especially to medical images acquired by Computed Tomography (CT). As the histogram equalization approach, this method is based on image histogram analysis. Yet, unlike the histogram equalization technique, it works on a selected range of the pixel intensity and is controlled by two parameters. Performance is tested on anonymous clinical CT series. Copyright © 2017 Elsevier Ltd. All rights reserved.

Stochastic HKMDHE: A multi-objective contrast enhancement algorithm

NASA Astrophysics Data System (ADS)

Pratiher, Sawon; Mukhopadhyay, Sabyasachi; Maity, Srideep; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2018-02-01

This contribution proposes a novel extension of the existing `Hyper Kurtosis based Modified Duo-Histogram Equalization' (HKMDHE) algorithm, for multi-objective contrast enhancement of biomedical images. A novel modified objective function has been formulated by joint optimization of the individual histogram equalization objectives. The optimal adequacy of the proposed methodology with respect to image quality metrics such as brightness preserving abilities, peak signal-to-noise ratio (PSNR), Structural Similarity Index (SSIM) and universal image quality metric has been experimentally validated. The performance analysis of the proposed Stochastic HKMDHE with existing histogram equalization methodologies like Global Histogram Equalization (GHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) has been given for comparative evaluation.

Infrared image segmentation method based on spatial coherence histogram and maximum entropy

NASA Astrophysics Data System (ADS)

Liu, Songtao; Shen, Tongsheng; Dai, Yao

2014-11-01

In order to segment the target well and suppress background noises effectively, an infrared image segmentation method based on spatial coherence histogram and maximum entropy is proposed. First, spatial coherence histogram is presented by weighting the importance of the different position of these pixels with the same gray-level, which is obtained by computing their local density. Then, after enhancing the image by spatial coherence histogram, 1D maximum entropy method is used to segment the image. The novel method can not only get better segmentation results, but also have a faster computation time than traditional 2D histogram-based segmentation methods.

Integration of g4tools in Geant4

NASA Astrophysics Data System (ADS)

Hřivnáčová, Ivana

2014-06-01

g4tools, that is originally part of the inlib and exlib packages, provides a very light and easy to install set of C++ classes that can be used to perform analysis in a Geant4 batch program. It allows to create and manipulate histograms and ntuples, and write them in supported file formats (ROOT, AIDA XML, CSV and HBOOK). It is integrated in Geant4 through analysis manager classes, thus providing a uniform interface to the g4tools objects and also hiding the differences between the classes for different supported output formats. Moreover, additional features, such as for example histogram activation or support for Geant4 units, are implemented in the analysis classes following users requests. A set of Geant4 user interface commands allows the user to create histograms and set their properties interactively or in Geant4 macros. g4tools was first introduced in the Geant4 9.5 release where its use was demonstrated in one basic example, and it is already used in a majority of the Geant4 examples within the Geant4 9.6 release. In this paper, we will give an overview and the present status of the integration of g4tools in Geant4 and report on upcoming new features.

Bin recycling strategy for improving the histogram precision on GPU

NASA Astrophysics Data System (ADS)

Cárdenas-Montes, Miguel; Rodríguez-Vázquez, Juan José; Vega-Rodríguez, Miguel A.

2016-07-01

Histogram is an easily comprehensible way to present data and analyses. In the current scientific context with access to large volumes of data, the processing time for building histogram has dramatically increased. For this reason, parallel construction is necessary to alleviate the impact of the processing time in the analysis activities. In this scenario, GPU computing is becoming widely used for reducing until affordable levels the processing time of histogram construction. Associated to the increment of the processing time, the implementations are stressed on the bin-count accuracy. Accuracy aspects due to the particularities of the implementations are not usually taken into consideration when building histogram with very large data sets. In this work, a bin recycling strategy to create an accuracy-aware implementation for building histogram on GPU is presented. In order to evaluate the approach, this strategy was applied to the computation of the three-point angular correlation function, which is a relevant function in Cosmology for the study of the Large Scale Structure of Universe. As a consequence of the study a high-accuracy implementation for histogram construction on GPU is proposed.

Statistical Analysis of Spectral Properties and Prosodic Parameters of Emotional Speech

NASA Astrophysics Data System (ADS)

Přibil, J.; Přibilová, A.

2009-01-01

The paper addresses reflection of microintonation and spectral properties in male and female acted emotional speech. Microintonation component of speech melody is analyzed regarding its spectral and statistical parameters. According to psychological research of emotional speech, different emotions are accompanied by different spectral noise. We control its amount by spectral flatness according to which the high frequency noise is mixed in voiced frames during cepstral speech synthesis. Our experiments are aimed at statistical analysis of cepstral coefficient values and ranges of spectral flatness in three emotions (joy, sadness, anger), and a neutral state for comparison. Calculated histograms of spectral flatness distribution are visually compared and modelled by Gamma probability distribution. Histograms of cepstral coefficient distribution are evaluated and compared using skewness and kurtosis. Achieved statistical results show good correlation comparing male and female voices for all emotional states portrayed by several Czech and Slovak professional actors.

ADC Histogram Analysis of Cervical Cancer Aids Detecting Lymphatic Metastases-a Preliminary Study.

PubMed

Schob, Stefan; Meyer, Hans Jonas; Pazaitis, Nikolaos; Schramm, Dominik; Bremicker, Kristina; Exner, Marc; Höhn, Anne Kathrin; Garnov, Nikita; Surov, Alexey

2017-12-01

Apparent diffusion coefficient (ADC) histogram analysis has been used to some extent in cervical cancer (CC) to distinguish between low-grade and high-grade tumors. Although this differentiation is undoubtedly helpful, it would be even more crucial in the presurgical setting to determine whether a tumor already gained the potential to metastasize via the lymphatic system. So far, no studies investigated the potential of 3T ADC histogram analysis in CC to differentiate between nodal-positive and nodal-negative entities. Therefore, the principal aim of our study was to investigate the potential of 3T ADC histogram analysis to differentiate between CC with and without lymph node metastasis. The second aim was to elucidate possible differences in ADC histogram parameters between CC with limited vs. advanced tumor stages and well-differentiated vs. undifferentiated lesions. Finally, correlations of p53 expression and Ki-67 index with ADC parameters were analyzed. Eighteen female patients (mean age 55.4 years, range 32-79 years) with histopathologically confirmed cervical squamous cell carcinoma of the uterine cervix were prospectively enrolled. Tumor stages, tumor grading, status of metastatic dissemination, Ki67-index, and p53 expression were assessed in these patients. Diffusion weighted imaging (DWI) was obtained in a 3T scanner using the following b values: b0 and b1000 s/mm 2 . Group comparisons using Mann-Whitney U test revealed the following findings: nodal-positive CC had statistically significant lower ADC parameters (ADCmin, ADCmean, median ADC, Mode, p10, p25, p75, and p90) in comparison to nodal-negative CC (all p < 0.05). ADCentropy was significantly elevated (p = 0.046) in tumors with advanced T stages (T3/4) compared to tumors with limited T stage (T2). ADCmin values were different in a statistically significant manner comparing G1/G2 and G3 tumors (40.45 ± 18.63 vs. 65.0 ± 23.63 × 10-5 mm2 s -1 , p = 0.035). Furthermore, Spearman Rho calculation identified an inverse correlation between ADCentropy and p53 expression (r = -0.472, p = 0.048). The main finding of our study is the discriminability of nodal-positive from nodal-negative CC using ADC histogram analysis in 3T DWI. This information is crucial for the gynecological surgeon to identify the optimal treatment strategy for patients suffering from CC. Furthermore, ADCentropy was identified as a potential imaging biomarker for tumor heterogeneity and might be able to indicate further molecular changes like loss of p53 expression, which is associated with EMT and consequentially indicates a poor prognosis in CC. Finally, our study confirmed the findings of previous works, which indicated that histogram analysis of ADC maps can distinguish between low-grade and high-grade CC. In conclusion, it can be stated that ADC histogram analysis provides additional, prognostically important information on tumor biology in CC.

AHIMSA - Ad hoc histogram information measure sensing algorithm for feature selection in the context of histogram inspired clustering techniques

NASA Technical Reports Server (NTRS)

Dasarathy, B. V.

1976-01-01

An algorithm is proposed for dimensionality reduction in the context of clustering techniques based on histogram analysis. The approach is based on an evaluation of the hills and valleys in the unidimensional histograms along the different features and provides an economical means of assessing the significance of the features in a nonparametric unsupervised data environment. The method has relevance to remote sensing applications.

Clinical Utility of Blood Cell Histogram Interpretation

PubMed Central

Bhagya, S.; Majeed, Abdul

2017-01-01

An automated haematology analyser provides blood cell histograms by plotting the sizes of different blood cells on X-axis and their relative number on Y-axis. Histogram interpretation needs careful analysis of Red Blood Cell (RBC), White Blood Cell (WBC) and platelet distribution curves. Histogram analysis is often a neglected part of the automated haemogram which if interpreted well, has significant potential to provide diagnostically relevant information even before higher level investigations are ordered. PMID:29207767

Clinical Utility of Blood Cell Histogram Interpretation.

PubMed

Thomas, E T Arun; Bhagya, S; Majeed, Abdul

2017-09-01

An automated haematology analyser provides blood cell histograms by plotting the sizes of different blood cells on X-axis and their relative number on Y-axis. Histogram interpretation needs careful analysis of Red Blood Cell (RBC), White Blood Cell (WBC) and platelet distribution curves. Histogram analysis is often a neglected part of the automated haemogram which if interpreted well, has significant potential to provide diagnostically relevant information even before higher level investigations are ordered.

Multipurpose contrast enhancement on epiphyseal plates and ossification centers for bone age assessment

PubMed Central

2013-01-01

Background The high variations of background luminance, low contrast and excessively enhanced contrast of hand bone radiograph often impede the bone age assessment rating system in evaluating the degree of epiphyseal plates and ossification centers development. The Global Histogram equalization (GHE) has been the most frequently adopted image contrast enhancement technique but the performance is not satisfying. A brightness and detail preserving histogram equalization method with good contrast enhancement effect has been a goal of much recent research in histogram equalization. Nevertheless, producing a well-balanced histogram equalized radiograph in terms of its brightness preservation, detail preservation and contrast enhancement is deemed to be a daunting task. Method In this paper, we propose a novel framework of histogram equalization with the aim of taking several desirable properties into account, namely the Multipurpose Beta Optimized Bi-Histogram Equalization (MBOBHE). This method performs the histogram optimization separately in both sub-histograms after the segmentation of histogram using an optimized separating point determined based on the regularization function constituted by three components. The result is then assessed by the qualitative and quantitative analysis to evaluate the essential aspects of histogram equalized image using a total of 160 hand radiographs that are implemented in testing and analyses which are acquired from hand bone online database. Result From the qualitative analysis, we found that basic bi-histogram equalizations are not capable of displaying the small features in image due to incorrect selection of separating point by focusing on only certain metric without considering the contrast enhancement and detail preservation. From the quantitative analysis, we found that MBOBHE correlates well with human visual perception, and this improvement shortens the evaluation time taken by inspector in assessing the bone age. Conclusions The proposed MBOBHE outperforms other existing methods regarding comprehensive performance of histogram equalization. All the features which are pertinent to bone age assessment are more protruding relative to other methods; this has shorten the required evaluation time in manual bone age assessment using TW method. While the accuracy remains unaffected or slightly better than using unprocessed original image. The holistic properties in terms of brightness preservation, detail preservation and contrast enhancement are simultaneous taken into consideration and thus the visual effect is contributive to manual inspection. PMID:23565999

Using histograms to introduce randomization in the generation of ensembles of decision trees

DOEpatents

Kamath, Chandrika; Cantu-Paz, Erick; Littau, David

2005-02-22

A system for decision tree ensembles that includes a module to read the data, a module to create a histogram, a module to evaluate a potential split according to some criterion using the histogram, a module to select a split point randomly in an interval around the best split, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method includes the steps of reading the data; creating a histogram; evaluating a potential split according to some criterion using the histogram, selecting a split point randomly in an interval around the best split, splitting the data, and combining multiple decision trees in ensembles.

Color Histogram Diffusion for Image Enhancement

NASA Technical Reports Server (NTRS)

Kim, Taemin

2011-01-01

Various color histogram equalization (CHE) methods have been proposed to extend grayscale histogram equalization (GHE) for color images. In this paper a new method called histogram diffusion that extends the GHE method to arbitrary dimensions is proposed. Ranges in a histogram are specified as overlapping bars of uniform heights and variable widths which are proportional to their frequencies. This diagram is called the vistogram. As an alternative approach to GHE, the squared error of the vistogram from the uniform distribution is minimized. Each bar in the vistogram is approximated by a Gaussian function. Gaussian particles in the vistoram diffuse as a nonlinear autonomous system of ordinary differential equations. CHE results of color images showed that the approach is effective.

High speed acquisition of multiparameter data using a Macintosh IIcx

NASA Astrophysics Data System (ADS)

Berno, Anthony; Vogel, John S.; Caffee, Marc

1991-05-01

Accelerator mass spectrometry systems based on > 3 MV tandem accelerators often use multianode ionization detectors and/or time-of-flight detectors to identify individual isotopes through multiparameter analysis. A Macintosh IIcx has been programmed to collect AMS data from a CAMAC-implemented analyzer and to display the histogrammed individual parameters and a doubleparameter array. The computer-CAMAC connection is through a NuBus to CAMAC dataway interface which allows direct addressing to all functions and registers in the crate. Asynchronous data from the rare isotope are sorted into a CAMAC memory module by a list sequence controller. Isotope switching is controlled by a one-cycle timing generator. A rate-dependent amount of time is used to transfer the data from the memory module at the end of each timing cycle. The present configuration uses 10-75 ms for rates of 500-10000 cps. Parameter analysis occurs during the rest of the 520 ms data collection cycle. Completed measurements of the isotope concentrations of each sample are written to files which are compatible with standard Macintosh databases or other processing programs. The system is inexpensive and operates at speeds comparable to those obtainable using larger computers.

Using the Bootstrap Method for a Statistical Significance Test of Differences between Summary Histograms

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2006-01-01

A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.

Computer user's manual for a generalized curve fit and plotting program

NASA Technical Reports Server (NTRS)

Schlagheck, R. A.; Beadle, B. D., II; Dolerhie, B. D., Jr.; Owen, J. W.

1973-01-01

A FORTRAN coded program has been developed for generating plotted output graphs on 8-1/2 by 11-inch paper. The program is designed to be used by engineers, scientists, and non-programming personnel on any IBM 1130 system that includes a 1627 plotter. The program has been written to provide a fast and efficient method of displaying plotted data without having to generate any additions. Various output options are available to the program user for displaying data in four different types of formatted plots. These options include discrete linear, continuous, and histogram graphical outputs. The manual contains information about the use and operation of this program. A mathematical description of the least squares goodness of fit test is presented. A program listing is also included.

A characterization of Parkinson's disease by describing the visual field motion during gait

NASA Astrophysics Data System (ADS)

Trujillo, David; Martínez, Fabio; Atehortúa, Angélica; Alvarez, Charlens; Romero, Eduardo

2015-12-01

An early diagnosis of Parkinson's Disease (PD) is crucial towards devising successful rehabilitation programs. Typically, the PD diagnosis is performed by characterizing typical symptoms, namely bradykinesia, rigidity, tremor, postural instability or freezing gait. However, traditional examination tests are usually incapable of detecting slight motor changes, specially for early stages of the pathology. Recently, eye movement abnormalities have correlated with early onset of some neurodegenerative disorders. This work introduces a new characterization of the Parkinson disease by describing the ocular motion during a common daily activity as the gait. This paper proposes a fully automatic eye motion analysis using a dense optical flow that tracks the ocular direction. The eye motion is then summarized using orientation histograms constructed during a whole gait cycle. The proposed approach was evaluated by measuring the χ2 distance between the orientation histograms, showing substantial differences between control and PD patients.

FPGA based charge fast histogramming for GEM detector

NASA Astrophysics Data System (ADS)

Poźniak, Krzysztof T.; Byszuk, A.; Chernyshova, M.; Cieszewski, R.; Czarski, T.; Dominik, W.; Jakubowska, K.; Kasprowicz, G.; Rzadkiewicz, J.; Scholz, M.; Zabolotny, W.

2013-10-01

This article presents a fast charge histogramming method for the position sensitive X-ray GEM detector. The energy resolved measurements are carried out simultaneously for 256 channels of the GEM detector. The whole process of histogramming is performed in 21 FPGA chips (Spartan-6 series from Xilinx) . The results of the histogramming process are stored in an external DDR3 memory. The structure of an electronic measuring equipment and a firmware functionality implemented in the FPGAs is described. Examples of test measurements are presented.

Local dynamic range compensation for scanning electron microscope imaging system.

PubMed

Sim, K S; Huang, Y H

2015-01-01

This is the extended project by introducing the modified dynamic range histogram modification (MDRHM) and is presented in this paper. This technique is used to enhance the scanning electron microscope (SEM) imaging system. By comparing with the conventional histogram modification compensators, this technique utilizes histogram profiling by extending the dynamic range of each tile of an image to the limit of 0-255 range while retains its histogram shape. The proposed technique yields better image compensation compared to conventional methods. © Wiley Periodicals, Inc.

MCNP output data analysis with ROOT (MODAR)

NASA Astrophysics Data System (ADS)

Carasco, C.

2010-12-01

MCNP Output Data Analysis with ROOT (MODAR) is a tool based on CERN's ROOT software. MODAR has been designed to handle time-energy data issued by MCNP simulations of neutron inspection devices using the associated particle technique. MODAR exploits ROOT's Graphical User Interface and functionalities to visualize and process MCNP simulation results in a fast and user-friendly way. MODAR allows to take into account the detection system time resolution (which is not possible with MCNP) as well as detectors energy response function and counting statistics in a straightforward way. New version program summaryProgram title: MODAR Catalogue identifier: AEGA_v1_1 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGA_v1_1.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 150 927 No. of bytes in distributed program, including test data, etc.: 4 981 633 Distribution format: tar.gz Programming language: C++ Computer: Most Unix workstations and PCs Operating system: Most Unix systems, Linux and windows, provided the ROOT package has been installed. Examples where tested under Suse Linux and Windows XP. RAM: Depends on the size of the MCNP output file. The example presented in the article, which involves three two dimensional 139×740 bins histograms, allocates about 60 MB. These data are running under ROOT and include consumption by ROOT itself. Classification: 17.6 Catalogue identifier of previous version: AEGA_v1_0 Journal reference of previous version: Comput. Phys. Comm. 181 (2010) 1161 External routines: ROOT version 5.24.00 ( http://root.cern.ch/drupal/) Does the new version supersede the previous version?: Yes Nature of problem: The output of a MCNP simulation is an ascii file. The data processing is usually performed by copying and pasting the relevant parts of the ascii file into Microsoft Excel. Such an approach is satisfactory when the quantity of data is small but is not efficient when the size of the simulated data is large, for example when time-energy correlations are studied in detail such as in problems involving the associated particle technique. In addition, since the finite time resolution of the simulated detector cannot be modeled with MCNP, systems in which time-energy correlation is crucial cannot be described in a satisfactory way. Finally, realistic particle energy deposit in detectors is calculated with MCNP in a two step process involving type-5 then type-8 tallies. In the first step, the photon flux energy spectrum associated to a time region is selected and serves as a source energy distribution for the second step. Thus, several files must be manipulated before getting the result, which can be time consuming if one needs to study several time regions or different detectors performances. In the same way, modeling counting statistics obtained in a limited acquisition time requires several steps and can also be time consuming. Solution method: In order to overcome the previous limitations, the MODAR C++ code has been written to make use of CERN's ROOT data analysis software. MCNP output data are read from the MCNP output file with dedicated routines. Two dimensional histograms are filled and can be handled efficiently within the ROOT framework. To keep a user friendly analysis tool, all processing and data display can be done by means of ROOT Graphical User Interface. Specific routines have been written to include detectors finite time resolution and energy response function as well as counting statistics in a straightforward way. Reasons for new version: For applications involving the Associate Particle Technique, a large number of gamma rays are produced by the fast neutrons interactions. To study the energy spectra, it is useful to identify the gamma-ray energy peaks in a straightforward way. Therefore, the possibility to show gamma rays corresponding to specific reactions has been added in MODAR. Summary of revisions: It is possible to use a gamma ray database to better identify in the energy spectra gamma ray peaks with their first and second escapes. Histograms can be scaled by the number of source particle to evaluate the number of counts that is expected without statistical uncertainties. Additional comments: The possibility of adding tallies has also been incorporated in MODAR in order to describe systems in which the signal from several detectors can be summed. Moreover, MODAR can be adapted to handle other problems involving two dimensional data. Running time: The CPU time needed to smear a two dimensional histogram depends on the size of the histogram. In the presented example, the time-energy smearing of one of the 139×740 two dimensional histograms takes 3 minutes with a DELL computer equipped with INTEL Core 2.

Whole-lesion apparent diffusion coefficient histogram analysis: significance in T and N staging of gastric cancers.

PubMed

Liu, Song; Zhang, Yujuan; Chen, Ling; Guan, Wenxian; Guan, Yue; Ge, Yun; He, Jian; Zhou, Zhengyang

2017-10-02

Whole-lesion apparent diffusion coefficient (ADC) histogram analysis has been introduced and proved effective in assessment of multiple tumors. However, the application of whole-volume ADC histogram analysis in gastrointestinal tumors has just started and never been reported in T and N staging of gastric cancers. Eighty patients with pathologically confirmed gastric carcinomas underwent diffusion weighted (DW) magnetic resonance imaging before surgery prospectively. Whole-lesion ADC histogram analysis was performed by two radiologists independently. The differences of ADC histogram parameters among different T and N stages were compared with independent-samples Kruskal-Wallis test. Receiver operating characteristic (ROC) analysis was performed to evaluate the performance of ADC histogram parameters in differentiating particular T or N stages of gastric cancers. There were significant differences of all the ADC histogram parameters for gastric cancers at different T (except ADC min and ADC max ) and N (except ADC max ) stages. Most ADC histogram parameters differed significantly between T1 vs T3, T1 vs T4, T2 vs T4, N0 vs N1, N0 vs N3, and some parameters (ADC 5% , ADC 10% , ADC min ) differed significantly between N0 vs N2, N2 vs N3 (all P < 0.05). Most parameters except ADC max performed well in differentiating different T and N stages of gastric cancers. Especially for identifying patients with and without lymph node metastasis, the ADC 10% yielded the largest area under the ROC curve of 0.794 (95% confidence interval, 0.677-0.911). All the parameters except ADC max showed excellent inter-observer agreement with intra-class correlation coefficients higher than 0.800. Whole-volume ADC histogram parameters held great potential in differentiating different T and N stages of gastric cancers preoperatively.

Histogram Profiling of Postcontrast T1-Weighted MRI Gives Valuable Insights into Tumor Biology and Enables Prediction of Growth Kinetics and Prognosis in Meningiomas.

PubMed

Gihr, Georg Alexander; Horvath-Rizea, Diana; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Henkes, Hans; Richter, Cindy; Hoffmann, Karl-Titus; Surov, Alexey; Schob, Stefan

2018-06-14

Meningiomas are the most frequently diagnosed intracranial masses, oftentimes requiring surgery. Especially procedure-related morbidity can be substantial, particularly in elderly patients. Hence, reliable imaging modalities enabling pretherapeutic prediction of tumor grade, growth kinetic, realistic prognosis, and-as a consequence-necessity of surgery are of great value. In this context, a promising diagnostic approach is advanced analysis of magnetic resonance imaging data. Therefore, our study investigated whether histogram profiling of routinely acquired postcontrast T1-weighted images is capable of separating low-grade from high-grade lesions and whether histogram parameters reflect Ki-67 expression in meningiomas. Pretreatment T1-weighted postcontrast volumes of 44 meningioma patients were used for signal intensity histogram profiling. WHO grade, tumor volume, and Ki-67 expression were evaluated. Comparative and correlative statistics investigating the association between histogram profile parameters and neuropathology were performed. None of the investigated histogram parameters revealed significant differences between low-grade and high-grade meningiomas. However, significant correlations were identified between Ki-67 and the histogram parameters skewness and entropy as well as between entropy and tumor volume. Contrary to previously reported findings, pretherapeutic postcontrast T1-weighted images can be used to predict growth kinetics in meningiomas if whole tumor histogram analysis is employed. However, no differences between distinct WHO grades were identifiable in out cohort. As a consequence, histogram analysis of postcontrast T1-weighted images is a promising approach to obtain quantitative in vivo biomarkers reflecting the proliferative potential in meningiomas. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Comparison of image enhancement methods for the effective diagnosis in successive whole-body bone scans.

PubMed

Jeong, Chang Bu; Kim, Kwang Gi; Kim, Tae Sung; Kim, Seok Ki

2011-06-01

Whole-body bone scan is one of the most frequent diagnostic procedures in nuclear medicine. Especially, it plays a significant role in important procedures such as the diagnosis of osseous metastasis and evaluation of osseous tumor response to chemotherapy and radiation therapy. It can also be used to monitor the possibility of any recurrence of the tumor. However, it is a very time-consuming effort for radiologists to quantify subtle interval changes between successive whole-body bone scans because of many variations such as intensity, geometry, and morphology. In this paper, we present the most effective method of image enhancement based on histograms, which may assist radiologists in interpreting successive whole-body bone scans effectively. Forty-eight successive whole-body bone scans from 10 patients were obtained and evaluated using six methods of image enhancement based on histograms: histogram equalization, brightness-preserving bi-histogram equalization, contrast-limited adaptive histogram equalization, end-in search, histogram matching, and exact histogram matching (EHM). Comparison of the results of the different methods was made using three similarity measures peak signal-to-noise ratio, histogram intersection, and structural similarity. Image enhancement of successive bone scans using EHM showed the best results out of the six methods measured for all similarity measures. EHM is the best method of image enhancement based on histograms for diagnosing successive whole-body bone scans. The method for successive whole-body bone scans has the potential to greatly assist radiologists quantify interval changes more accurately and quickly by compensating for the variable nature of intensity information. Consequently, it can improve radiologists' diagnostic accuracy as well as reduce reading time for detecting interval changes.

Dose-volume histogram prediction using density estimation.

PubMed

Skarpman Munter, Johanna; Sjölund, Jens

2015-09-07

Knowledge of what dose-volume histograms can be expected for a previously unseen patient could increase consistency and quality in radiotherapy treatment planning. We propose a machine learning method that uses previous treatment plans to predict such dose-volume histograms. The key to the approach is the framing of dose-volume histograms in a probabilistic setting.The training consists of estimating, from the patients in the training set, the joint probability distribution of some predictive features and the dose. The joint distribution immediately provides an estimate of the conditional probability of the dose given the values of the predictive features. The prediction consists of estimating, from the new patient, the distribution of the predictive features and marginalizing the conditional probability from the training over this. Integrating the resulting probability distribution for the dose yields an estimate of the dose-volume histogram.To illustrate how the proposed method relates to previously proposed methods, we use the signed distance to the target boundary as a single predictive feature. As a proof-of-concept, we predicted dose-volume histograms for the brainstems of 22 acoustic schwannoma patients treated with stereotactic radiosurgery, and for the lungs of 9 lung cancer patients treated with stereotactic body radiation therapy. Comparing with two previous attempts at dose-volume histogram prediction we find that, given the same input data, the predictions are similar.In summary, we propose a method for dose-volume histogram prediction that exploits the intrinsic probabilistic properties of dose-volume histograms. We argue that the proposed method makes up for some deficiencies in previously proposed methods, thereby potentially increasing ease of use, flexibility and ability to perform well with small amounts of training data.

Structure Size Enhanced Histogram

NASA Astrophysics Data System (ADS)

Wesarg, Stefan; Kirschner, Matthias

Direct volume visualization requires the definition of transfer functions (TFs) for the assignment of opacity and color. Multi-dimensional TFs are based on at least two image properties, and are specified by means of 2D histograms. In this work we propose a new type of a 2D histogram which combines gray value with information about the size of the structures. This structure size enhanced (SSE) histogram is an intuitive approach for representing anatomical features. Clinicians — the users we are focusing on — are much more familiar with selecting features by their size than by their gradient magnitude value. As a proof of concept, we employ the SSE histogram for the definition of two-dimensional TFs for the visualization of 3D MRI and CT image data.

Face recognition algorithm using extended vector quantization histogram features.

PubMed

Yan, Yan; Lee, Feifei; Wu, Xueqian; Chen, Qiu

2018-01-01

In this paper, we propose a face recognition algorithm based on a combination of vector quantization (VQ) and Markov stationary features (MSF). The VQ algorithm has been shown to be an effective method for generating features; it extracts a codevector histogram as a facial feature representation for face recognition. Still, the VQ histogram features are unable to convey spatial structural information, which to some extent limits their usefulness in discrimination. To alleviate this limitation of VQ histograms, we utilize Markov stationary features (MSF) to extend the VQ histogram-based features so as to add spatial structural information. We demonstrate the effectiveness of our proposed algorithm by achieving recognition results superior to those of several state-of-the-art methods on publicly available face databases.

Ultrasonic histogram assessment of early response to concurrent chemo-radiotherapy in patients with locally advanced cervical cancer: a feasibility study.

PubMed

Xu, Yan; Ru, Tong; Zhu, Lijing; Liu, Baorui; Wang, Huanhuan; Zhu, Li; He, Jian; Liu, Song; Zhou, Zhengyang; Yang, Xiaofeng

To monitor early response for locally advanced cervical cancers undergoing concurrent chemo-radiotherapy (CCRT) by ultrasonic histogram. B-mode ultrasound examinations were performed at 4 time points in thirty-four patients during CCRT. Six ultrasonic histogram parameters were used to assess the echogenicity, homogeneity and heterogeneity of tumors. I peak increased rapidly since the first week after therapy initiation, whereas W low , W high and A high changed significantly at the second week. The average ultrasonic histogram progressively moved toward the right and converted into more symmetrical shape. Ultrasonic histogram could be served as a potential marker to monitor early response during CCRT. Copyright © 2018 Elsevier Inc. All rights reserved.

Face verification system for Android mobile devices using histogram based features

NASA Astrophysics Data System (ADS)

Sato, Sho; Kobayashi, Kazuhiro; Chen, Qiu

2016-07-01

This paper proposes a face verification system that runs on Android mobile devices. In this system, facial image is captured by a built-in camera on the Android device firstly, and then face detection is implemented using Haar-like features and AdaBoost learning algorithm. The proposed system verify the detected face using histogram based features, which are generated by binary Vector Quantization (VQ) histogram using DCT coefficients in low frequency domains, as well as Improved Local Binary Pattern (Improved LBP) histogram in spatial domain. Verification results with different type of histogram based features are first obtained separately and then combined by weighted averaging. We evaluate our proposed algorithm by using publicly available ORL database and facial images captured by an Android tablet.

Breast density evaluation using spectral mammography, radiologist reader assessment and segmentation techniques: a retrospective study based on left and right breast comparison

PubMed Central

Molloi, Sabee; Ding, Huanjun; Feig, Stephen

2015-01-01

Purpose The purpose of this study was to compare the precision of mammographic breast density measurement using radiologist reader assessment, histogram threshold segmentation, fuzzy C-mean segmentation and spectral material decomposition. Materials and Methods Spectral mammography images from a total of 92 consecutive asymptomatic women (50–69 years old) who presented for annual screening mammography were retrospectively analyzed for this study. Breast density was estimated using 10 radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm and spectral material decomposition. The breast density correlation between left and right breasts was used to assess the precision of these techniques to measure breast composition relative to dual-energy material decomposition. Results In comparison to the other techniques, the results of breast density measurements using dual-energy material decomposition showed the highest correlation. The relative standard error of estimate for breast density measurements from left and right breasts using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm and dual-energy material decomposition was calculated to be 1.95, 2.87, 2.07 and 1.00, respectively. Conclusion The results indicate that the precision of dual-energy material decomposition was approximately factor of two higher than the other techniques with regard to better correlation of breast density measurements from right and left breasts. PMID:26031229

Combining Vector Quantization and Histogram Equalization.

ERIC Educational Resources Information Center

Cosman, Pamela C.; And Others

1992-01-01

Discussion of contrast enhancement techniques focuses on the use of histogram equalization with a data compression technique, i.e., tree-structured vector quantization. The enhancement technique of intensity windowing is described, and the use of enhancement techniques for medical images is explained, including adaptive histogram equalization.…

Histogram and gray level co-occurrence matrix on gray-scale ultrasound images for diagnosing lymphocytic thyroiditis.

PubMed

Shin, Young Gyung; Yoo, Jaeheung; Kwon, Hyeong Ju; Hong, Jung Hwa; Lee, Hye Sun; Yoon, Jung Hyun; Kim, Eun-Kyung; Moon, Hee Jung; Han, Kyunghwa; Kwak, Jin Young

2016-08-01

The objective of the study was to evaluate whether texture analysis using histogram and gray level co-occurrence matrix (GLCM) parameters can help clinicians diagnose lymphocytic thyroiditis (LT) and differentiate LT according to pathologic grade. The background thyroid pathology of 441 patients was classified into no evidence of LT, chronic LT (CLT), and Hashimoto's thyroiditis (HT). Histogram and GLCM parameters were extracted from the regions of interest on ultrasound. The diagnostic performances of the parameters for diagnosing and differentiating LT were calculated. Of the histogram and GLCM parameters, the mean on histogram had the highest Az (0.63) and VUS (0.303). As the degrees of LT increased, the mean decreased and the standard deviation and entropy increased. The mean on histogram from gray-scale ultrasound showed the best diagnostic performance as a single parameter in differentiating LT according to pathologic grade as well as in diagnosing LT. Copyright © 2016 Elsevier Ltd. All rights reserved.

Whole-Lesion Histogram Analysis of Apparent Diffusion Coefficient for the Assessment of Cervical Cancer.

PubMed

Guan, Yue; Shi, Hua; Chen, Ying; Liu, Song; Li, Weifeng; Jiang, Zhuoran; Wang, Huanhuan; He, Jian; Zhou, Zhengyang; Ge, Yun

2016-01-01

The aim of this study was to explore the application of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) values of cervical cancer. A total of 54 women (mean age, 53 years) with cervical cancers underwent 3-T diffusion-weighted imaging with b values of 0 and 800 s/mm prospectively. Whole-lesion histogram analysis of ADC values was performed. Paired sample t test was used to compare differences in ADC histogram parameters between cervical cancers and normal cervical tissues. Receiver operating characteristic curves were constructed to identify the optimal threshold of each parameter. All histogram parameters in this study including ADCmean, ADCmin, ADC10%-ADC90%, mode, skewness, and kurtosis of cervical cancers were significantly lower than those of normal cervical tissues (all P < 0.0001). ADC90% had the largest area under receiver operating characteristic curve of 0.996. Whole-lesion histogram analysis of ADC maps is useful in the assessment of cervical cancer.

Time-cumulated visible and infrared radiance histograms used as descriptors of surface and cloud variations

NASA Technical Reports Server (NTRS)

Seze, Genevieve; Rossow, William B.

1991-01-01

The spatial and temporal stability of the distributions of satellite-measured visible and infrared radiances, caused by variations in clouds and surfaces, are investigated using bidimensional and monodimensional histograms and time-composite images. Similar analysis of the histograms of the original and time-composite images provides separation of the contributions of the space and time variations to the total variations. The variability of both the surfaces and clouds is found to be larger at scales much larger than the minimum resolved by satellite imagery. This study shows that the shapes of these histograms are distinctive characteristics of the different climate regimes and that particular attributes of these histograms can be related to several general, though not universal, properties of clouds and surface variations at regional and synoptic scales. There are also significant exceptions to these relationships in particular climate regimes. The characteristics of these radiance histograms provide a stable well defined descriptor of the cloud and surface properties.

Particle swarm optimization-based local entropy weighted histogram equalization for infrared image enhancement

NASA Astrophysics Data System (ADS)

Wan, Minjie; Gu, Guohua; Qian, Weixian; Ren, Kan; Chen, Qian; Maldague, Xavier

2018-06-01

Infrared image enhancement plays a significant role in intelligent urban surveillance systems for smart city applications. Unlike existing methods only exaggerating the global contrast, we propose a particle swam optimization-based local entropy weighted histogram equalization which involves the enhancement of both local details and fore-and background contrast. First of all, a novel local entropy weighted histogram depicting the distribution of detail information is calculated based on a modified hyperbolic tangent function. Then, the histogram is divided into two parts via a threshold maximizing the inter-class variance in order to improve the contrasts of foreground and background, respectively. To avoid over-enhancement and noise amplification, double plateau thresholds of the presented histogram are formulated by means of particle swarm optimization algorithm. Lastly, each sub-image is equalized independently according to the constrained sub-local entropy weighted histogram. Comparative experiments implemented on real infrared images prove that our algorithm outperforms other state-of-the-art methods in terms of both visual and quantized evaluations.

Apparent diffusion coefficient histogram shape analysis for monitoring early response in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy.

PubMed

Meng, Jie; Zhu, Lijing; Zhu, Li; Wang, Huanhuan; Liu, Song; Yan, Jing; Liu, Baorui; Guan, Yue; Ge, Yun; He, Jian; Zhou, Zhengyang; Yang, Xiaofeng

2016-10-22

To explore the role of apparent diffusion coefficient (ADC) histogram shape related parameters in early assessment of treatment response during the concurrent chemo-radiotherapy (CCRT) course of advanced cervical cancers. This prospective study was approved by the local ethics committee and informed consent was obtained from all patients. Thirty-two patients with advanced cervical squamous cell carcinomas underwent diffusion weighted magnetic resonance imaging (b values, 0 and 800 s/mm 2 ) before CCRT, at the end of 2nd and 4th week during CCRT and immediately after CCRT completion. Whole lesion ADC histogram analysis generated several histogram shape related parameters including skewness, kurtosis, s-sD av , width, standard deviation, as well as first-order entropy and second-order entropies. The averaged ADC histograms of 32 patients were generated to visually observe dynamic changes of the histogram shape following CCRT. All parameters except width and standard deviation showed significant changes during CCRT (all P < 0.05), and their variation trends fell into four different patterns. Skewness and kurtosis both showed high early decline rate (43.10 %, 48.29 %) at the end of 2nd week of CCRT. All entropies kept decreasing significantly since 2 weeks after CCRT initiated. The shape of averaged ADC histogram also changed obviously following CCRT. ADC histogram shape analysis held the potential in monitoring early tumor response in patients with advanced cervical cancers undergoing CCRT.

[Clinical application of MRI histogram in evaluation of muscle fatty infiltration].

PubMed

Zheng, Y M; Du, J; Li, W Z; Wang, Z X; Zhang, W; Xiao, J X; Yuan, Y

2016-10-18

To describe a method based on analysis of the histogram of intensity values produced from the magnetic resonance imaging (MRI) for quantifying the degree of fatty infiltration. The study included 25 patients with dystrophinopathy. All the subjects underwent muscle MRI test at thigh level. The histogram M values of 250 muscles adjusted for subcutaneous fat, representing the degree of fatty infiltration, were compared with the expert visual reading using the modified Mercuri scale. There was a significant positive correlation between the histogram M values and the scores of visual reading (r=0.854, P<0.001). The distinct pattern of muscle involvement detected in the patients with dystrophinopathy in our study of histogram M values was similar to that of visual reading and results in literature. The histogram M values had stronger correlations with the clinical data than the scores of visual reading as follows: the correlations with age (r=0.730, P<0.001) and (r=0.753, P<0.001); with strength of knee extensor (r=-0.468, P=0.024) and (r=-0.460, P=0.027) respectively. Meanwhile, the histogram M values analysis had better repeatability than visual reading with the interclass correlation coefficient was 0.998 (95% CI: 0.997-0.998, P<0.001) and 0.958 (95% CI: 0.946-0.967, P<0.001) respectively. Histogram M values analysis of MRI with the advantages of repeatability and objectivity can be used to evaluate the degree of muscle fatty infiltration.

Dissimilarity representations in lung parenchyma classification

NASA Astrophysics Data System (ADS)

Sørensen, Lauge; de Bruijne, Marleen

2009-02-01

A good problem representation is important for a pattern recognition system to be successful. The traditional approach to statistical pattern recognition is feature representation. More specifically, objects are represented by a number of features in a feature vector space, and classifiers are built in this representation. This is also the general trend in lung parenchyma classification in computed tomography (CT) images, where the features often are measures on feature histograms. Instead, we propose to build normal density based classifiers in dissimilarity representations for lung parenchyma classification. This allows for the classifiers to work on dissimilarities between objects, which might be a more natural way of representing lung parenchyma. In this context, dissimilarity is defined between CT regions of interest (ROI)s. ROIs are represented by their CT attenuation histogram and ROI dissimilarity is defined as a histogram dissimilarity measure between the attenuation histograms. In this setting, the full histograms are utilized according to the chosen histogram dissimilarity measure. We apply this idea to classification of different emphysema patterns as well as normal, healthy tissue. Two dissimilarity representation approaches as well as different histogram dissimilarity measures are considered. The approaches are evaluated on a set of 168 CT ROIs using normal density based classifiers all showing good performance. Compared to using histogram dissimilarity directly as distance in a emph{k} nearest neighbor classifier, which achieves a classification accuracy of 92.9%, the best dissimilarity representation based classifier is significantly better with a classification accuracy of 97.0% (text{emph{p" border="0" class="imgtopleft"> = 0.046).

Study of spectral/radiometric characteristics of the Thematic Mapper for land use applications

NASA Technical Reports Server (NTRS)

Malila, W. A.; Metzler, M. D. (Principal Investigator)

1985-01-01

Progress during ERIM's tenth quarter of effort under the LANDSAT-4 and 5 Image Data Quality Assessment program for the Thematic Mapper is described. Coincident LANDSAT-4 and 5 fully corrected (CCT-PT) TM data are analyzed in more detail and revised band-by-band relationships between the two sensors derived. An analysis technique employing the matching of cumulative distributions is developed and used and is believed to offer advantages over the histogram matching procedure currently used to produce LANDSAT data. Multiplicative factors ranging from 0.987 to 1.145 and offsets ranging from -2.7 to -6.2 video quantum levels are required to cause LANDSAT-5 data to match LANDSAT-4 data values. Evidence of low level clipping is found in TM Bands 5 and 7 of LANDSAT-5 but not LANDSAT-4. Analysis of the information content of LANDSAT TM and MSS data is continued. Components of information loss are identified and quantified and the effects of coarsened quantization are explored.

The Histogram-Area Connection

ERIC Educational Resources Information Center

Gratzer, William; Carpenter, James E.

2008-01-01

This article demonstrates an alternative approach to the construction of histograms--one based on the notion of using area to represent relative density in intervals of unequal length. The resulting histograms illustrate the connection between the area of the rectangles associated with particular outcomes and the relative frequency (probability)…

Investigating Student Understanding of Histograms

ERIC Educational Resources Information Center

Kaplan, Jennifer J.; Gabrosek, John G.; Curtiss, Phyllis; Malone, Chris

2014-01-01

Histograms are adept at revealing the distribution of data values, especially the shape of the distribution and any outlier values. They are included in introductory statistics texts, research methods texts, and in the popular press, yet students often have difficulty interpreting the information conveyed by a histogram. This research identifies…

Thresholding histogram equalization.

PubMed

Chuang, K S; Chen, S; Hwang, I M

2001-12-01

The drawbacks of adaptive histogram equalization techniques are the loss of definition on the edges of the object and overenhancement of noise in the images. These drawbacks can be avoided if the noise is excluded in the equalization transformation function computation. A method has been developed to separate the histogram into zones, each with its own equalization transformation. This method can be used to suppress the nonanatomic noise and enhance only certain parts of the object. This method can be combined with other adaptive histogram equalization techniques. Preliminary results indicate that this method can produce images with superior contrast.

Complexity of possibly gapped histogram and analysis of histogram.

PubMed

Fushing, Hsieh; Roy, Tania

2018-02-01

We demonstrate that gaps and distributional patterns embedded within real-valued measurements are inseparable biological and mechanistic information contents of the system. Such patterns are discovered through data-driven possibly gapped histogram, which further leads to the geometry-based analysis of histogram (ANOHT). Constructing a possibly gapped histogram is a complex problem of statistical mechanics due to the ensemble of candidate histograms being captured by a two-layer Ising model. This construction is also a distinctive problem of Information Theory from the perspective of data compression via uniformity. By defining a Hamiltonian (or energy) as a sum of total coding lengths of boundaries and total decoding errors within bins, this issue of computing the minimum energy macroscopic states is surprisingly resolved by applying the hierarchical clustering algorithm. Thus, a possibly gapped histogram corresponds to a macro-state. And then the first phase of ANOHT is developed for simultaneous comparison of multiple treatments, while the second phase of ANOHT is developed based on classical empirical process theory for a tree-geometry that can check the authenticity of branches of the treatment tree. The well-known Iris data are used to illustrate our technical developments. Also, a large baseball pitching dataset and a heavily right-censored divorce data are analysed to showcase the existential gaps and utilities of ANOHT.

Histogram-based quantitative evaluation of endobronchial ultrasonography images of peripheral pulmonary lesion.

PubMed

Morikawa, Kei; Kurimoto, Noriaki; Inoue, Takeo; Mineshita, Masamichi; Miyazawa, Teruomi

2015-01-01

Endobronchial ultrasonography using a guide sheath (EBUS-GS) is an increasingly common bronchoscopic technique, but currently, no methods have been established to quantitatively evaluate EBUS images of peripheral pulmonary lesions. The purpose of this study was to evaluate whether histogram data collected from EBUS-GS images can contribute to the diagnosis of lung cancer. Histogram-based analyses focusing on the brightness of EBUS images were retrospectively conducted: 60 patients (38 lung cancer; 22 inflammatory diseases), with clear EBUS images were included. For each patient, a 400-pixel region of interest was selected, typically located at a 3- to 5-mm radius from the probe, from recorded EBUS images during bronchoscopy. Histogram height, width, height/width ratio, standard deviation, kurtosis and skewness were investigated as diagnostic indicators. Median histogram height, width, height/width ratio and standard deviation were significantly different between lung cancer and benign lesions (all p < 0.01). With a cutoff value for standard deviation of 10.5, lung cancer could be diagnosed with an accuracy of 81.7%. Other characteristics investigated were inferior when compared to histogram standard deviation. Histogram standard deviation appears to be the most useful characteristic for diagnosing lung cancer using EBUS images. © 2015 S. Karger AG, Basel.

Complexity of possibly gapped histogram and analysis of histogram

PubMed Central

Roy, Tania

2018-01-01

We demonstrate that gaps and distributional patterns embedded within real-valued measurements are inseparable biological and mechanistic information contents of the system. Such patterns are discovered through data-driven possibly gapped histogram, which further leads to the geometry-based analysis of histogram (ANOHT). Constructing a possibly gapped histogram is a complex problem of statistical mechanics due to the ensemble of candidate histograms being captured by a two-layer Ising model. This construction is also a distinctive problem of Information Theory from the perspective of data compression via uniformity. By defining a Hamiltonian (or energy) as a sum of total coding lengths of boundaries and total decoding errors within bins, this issue of computing the minimum energy macroscopic states is surprisingly resolved by applying the hierarchical clustering algorithm. Thus, a possibly gapped histogram corresponds to a macro-state. And then the first phase of ANOHT is developed for simultaneous comparison of multiple treatments, while the second phase of ANOHT is developed based on classical empirical process theory for a tree-geometry that can check the authenticity of branches of the treatment tree. The well-known Iris data are used to illustrate our technical developments. Also, a large baseball pitching dataset and a heavily right-censored divorce data are analysed to showcase the existential gaps and utilities of ANOHT. PMID:29515829

Complexity of possibly gapped histogram and analysis of histogram

NASA Astrophysics Data System (ADS)

Fushing, Hsieh; Roy, Tania

2018-02-01

We demonstrate that gaps and distributional patterns embedded within real-valued measurements are inseparable biological and mechanistic information contents of the system. Such patterns are discovered through data-driven possibly gapped histogram, which further leads to the geometry-based analysis of histogram (ANOHT). Constructing a possibly gapped histogram is a complex problem of statistical mechanics due to the ensemble of candidate histograms being captured by a two-layer Ising model. This construction is also a distinctive problem of Information Theory from the perspective of data compression via uniformity. By defining a Hamiltonian (or energy) as a sum of total coding lengths of boundaries and total decoding errors within bins, this issue of computing the minimum energy macroscopic states is surprisingly resolved by applying the hierarchical clustering algorithm. Thus, a possibly gapped histogram corresponds to a macro-state. And then the first phase of ANOHT is developed for simultaneous comparison of multiple treatments, while the second phase of ANOHT is developed based on classical empirical process theory for a tree-geometry that can check the authenticity of branches of the treatment tree. The well-known Iris data are used to illustrate our technical developments. Also, a large baseball pitching dataset and a heavily right-censored divorce data are analysed to showcase the existential gaps and utilities of ANOHT.

Statistical techniques applied to aerial radiometric surveys (STAARS): principal components analysis user's manual. [NURE program

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

Koch, C.D.; Pirkle, F.L.; Schmidt, J.S.

1981-01-01

A Principal Components Analysis (PCA) has been written to aid in the interpretation of multivariate aerial radiometric data collected by the US Department of Energy (DOE) under the National Uranium Resource Evaluation (NURE) program. The variations exhibited by these data have been reduced and classified into a number of linear combinations by using the PCA program. The PCA program then generates histograms and outlier maps of the individual variates. Black and white plots can be made on a Calcomp plotter by the application of follow-up programs. All programs referred to in this guide were written for a DEC-10. From thismore » analysis a geologist may begin to interpret the data structure. Insight into geological processes underlying the data may be obtained.« less

Milwaukee Longitudinal School Choice Evaluation: Annual School Testing Summary Report 2009-10. SCDP Milwaukee Evaluation. Report # 26

ERIC Educational Resources Information Center

McShane, Michael Q.; Wolf, Patrick J.

2011-01-01

The purpose of this report is to provide descriptive data regarding the test scores of Milwaukee Parental Choice Program (MPCP) students in grades 4, 8 and 10 in reading, math and science, as reported to the School Choice Demonstration Project 2009-2010. The tables, graphs, and histograms presented in this report provide a snapshot of these…

Milwaukee Longitudinal School Choice Evaluation: Annual School Testing Summary Report 2008-09. SCDP Milwaukee Evaluation Report #18

ERIC Educational Resources Information Center

Dean, Jeffery R.; Wolf, Patrick J.

2010-01-01

The purpose of this report is to provide descriptive data regarding the test scores of Milwaukee Parental Choice Program (MPCP) students in grades 4, 8 and 10 in reading, math, and science, as reported to the School Choice Demonstration Project 2008-2009. The tables, graphs, and histograms presented in this paper provide a snapshot of these…

Milwaukee Longitudinal School Choice Evaluation: Annual School Testing Summary Report 2007-08. SCDP Milwaukee Evaluation Report #9

ERIC Educational Resources Information Center

Gray, Nathan L.; Wolf, Patrick J.; Jensen, Laura I.

2009-01-01

The purpose of this report is to provide descriptive data regarding the test scores of Milwaukee Parental Choice Program (MPCP) students in grades 4, 8 and 10 in reading, math and science, as reported to the School Choice Demonstration Project 2007-2008. The tables, graphs, and histograms presented in this report provide a snapshot of these…

PIRATE: pediatric imaging response assessment and targeting environment

NASA Astrophysics Data System (ADS)

Glenn, Russell; Zhang, Yong; Krasin, Matthew; Hua, Chiaho

2010-02-01

By combining the strengths of various imaging modalities, the multimodality imaging approach has potential to improve tumor staging, delineation of tumor boundaries, chemo-radiotherapy regime design, and treatment response assessment in cancer management. To address the urgent needs for efficient tools to analyze large-scale clinical trial data, we have developed an integrated multimodality, functional and anatomical imaging analysis software package for target definition and therapy response assessment in pediatric radiotherapy (RT) patients. Our software provides quantitative tools for automated image segmentation, region-of-interest (ROI) histogram analysis, spatial volume-of-interest (VOI) analysis, and voxel-wise correlation across modalities. To demonstrate the clinical applicability of this software, histogram analyses were performed on baseline and follow-up 18F-fluorodeoxyglucose (18F-FDG) PET images of nine patients with rhabdomyosarcoma enrolled in an institutional clinical trial at St. Jude Children's Research Hospital. In addition, we combined 18F-FDG PET, dynamic-contrast-enhanced (DCE) MR, and anatomical MR data to visualize the heterogeneity in tumor pathophysiology with the ultimate goal of adaptive targeting of regions with high tumor burden. Our software is able to simultaneously analyze multimodality images across multiple time points, which could greatly speed up the analysis of large-scale clinical trial data and validation of potential imaging biomarkers.

Three-dimensional volumetric gray-scale uterine cervix histogram prediction of days to delivery in full term pregnancy.

PubMed

Kim, Ji Youn; Kim, Hai-Joong; Hahn, Meong Hi; Jeon, Hye Jin; Cho, Geum Joon; Hong, Sun Chul; Oh, Min Jeong

2013-09-01

Our aim was to figure out whether volumetric gray-scale histogram difference between anterior and posterior cervix can indicate the extent of cervical consistency. We collected data of 95 patients who were appropriate for vaginal delivery with 36th to 37th weeks of gestational age from September 2010 to October 2011 in the Department of Obstetrics and Gynecology, Korea University Ansan Hospital. Patients were excluded who had one of the followings: Cesarean section, labor induction, premature rupture of membrane. Thirty-four patients were finally enrolled. The patients underwent evaluation of the cervix through Bishop score, cervical length, cervical volume, three-dimensional (3D) cervical volumetric gray-scale histogram. The interval days from the cervix evaluation to the delivery day were counted. We compared to 3D cervical volumetric gray-scale histogram, Bishop score, cervical length, cervical volume with interval days from the evaluation of the cervix to the delivery. Gray-scale histogram difference between anterior and posterior cervix was significantly correlated to days to delivery. Its correlation coefficient (R) was 0.500 (P = 0.003). The cervical length was significantly related to the days to delivery. The correlation coefficient (R) and P-value between them were 0.421 and 0.013. However, anterior lip histogram, posterior lip histogram, total cervical volume, Bishop score were not associated with days to delivery (P >0.05). By using gray-scale histogram difference between anterior and posterior cervix and cervical length correlated with the days to delivery. These methods can be utilized to better help predict a cervical consistency.

Construction and Evaluation of Histograms in Teacher Training

ERIC Educational Resources Information Center

Bruno, A.; Espinel, M. C.

2009-01-01

This article details the results of a written test designed to reveal how education majors construct and evaluate histograms and frequency polygons. Included is a description of the mistakes made by the students which shows how they tend to confuse histograms with bar diagrams, incorrectly assign data along the Cartesian axes and experience…

Empirical Histograms in Item Response Theory with Ordinal Data

ERIC Educational Resources Information Center

Woods, Carol M.

2007-01-01

The purpose of this research is to describe, test, and illustrate a new implementation of the empirical histogram (EH) method for ordinal items. The EH method involves the estimation of item response model parameters simultaneously with the approximation of the distribution of the random latent variable (theta) as a histogram. Software for the EH…

Symbol recognition via statistical integration of pixel-level constraint histograms: a new descriptor.

PubMed

Yang, Su

2005-02-01

A new descriptor for symbol recognition is proposed. 1) A histogram is constructed for every pixel to figure out the distribution of the constraints among the other pixels. 2) All the histograms are statistically integrated to form a feature vector with fixed dimension. The robustness and invariance were experimentally confirmed.

Airborne gamma-ray spectrometer and magnetometer survey, Durango D, Colorado. Final report Volume II A. Detail area

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

Not Available

1983-01-01

This volume contains geology of the Durango D detail area, radioactive mineral occurrences in Colorado, and geophysical data interpretation. Eight appendices provide: stacked profiles, geologic histograms, geochemical histograms, speed and altitude histograms, geologic statistical tables, geochemical statistical tables, magnetic and ancillary profiles, and test line data.

Airborne gamma-ray spectrometer and magnetometer survey, Durango C, Colorado. Final report Volume II A. Detail area

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

Not Available

1983-01-01

Geology of Durango C detail area, radioactive mineral occurrences in Colorado, and geophysical data interpretation are included in this report. Eight appendices provide: stacked profiles, geologic histograms, geochemical histograms, speed and altitude histograms, geologic statistical tables, magnetic and ancillary profiles, and test line data.

Action recognition via cumulative histogram of multiple features

NASA Astrophysics Data System (ADS)

Yan, Xunshi; Luo, Yupin

2011-01-01

Spatial-temporal interest points (STIPs) are popular in human action recognition. However, they suffer from difficulties in determining size of codebook and losing much information during forming histograms. In this paper, spatial-temporal interest regions (STIRs) are proposed, which are based on STIPs and are capable of marking the locations of the most ``shining'' human body parts. In order to represent human actions, the proposed approach takes great advantages of multiple features, including STIRs, pyramid histogram of oriented gradients and pyramid histogram of oriented optical flows. To achieve this, cumulative histogram is used to integrate dynamic information in sequences and to form feature vectors. Furthermore, the widely used nearest neighbor and AdaBoost methods are employed as classification algorithms. Experiments on public datasets KTH, Weizmann and UCF sports show that the proposed approach achieves effective and robust results.

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

Shin, D; Kang, S; Kim, D

Purpose: The dose difference between three-dimensional dose (3D dose) and 4D dose which considers motion due to respiratory can be varied according to geometrical relationship between planning target volume (PTV) and organ at risk (OAR). The purpose of the study is to investigate the dose difference between 3D and 4D dose using overlap volume histogram (OVH) which is an indicator that quantify geometrical relationship between a PTV and an OAR. Methods: Five liver cancer patients who previously treated stereotactic body radiotherapy (SBRT) were investigated. Four-dimensional computed tomography (4DCT) images were acquired for all patients. ITV-based treatment planning was performed. 3Dmore » dose was calculated on the end-exhale phase image as a reference phase image. 4D dose accumulation was implemented from all phase images using dose warping technique used deformable image registration (DIR) algorithm (Horn and Schunck optical flow) in DIRART. In this study OVH was used to quantify geometrical relationship between a PTV and an OAR. OVH between a PTV and a selected OAR was generated for each patient case and compared for all cases. The dose difference between 3D and 4D dose for normal organ was calculated and compared for all cases according to OVH. Results: The 3D and 4D dose difference for OAR was analyzed using dose-volume histogram (DVH). On the basis of a specific point which corresponds to 10% of OAR volume overlapped with expanded PTV, mean dose difference was 34.56% in minimum OVH distance case and 13.36% in maximum OVH distance case. As the OVH distance increased, mean dose difference between 4D and 3D dose was decreased. Conclusion: The tendency of dose difference variation was verified according to OVH. OVH is seems to be indicator that has a potential to predict the dose difference between 4D and 3D dose. This work was supported by the Radiation Technology R&D program (No. 2013M2A2A7043498) and the Mid-career Researcher Program (2014R1A2A1A10050270) through the National Research Foundation of Korea funded by the Ministry of Science, ICT&Future Planning.« less

VICAR - VIDEO IMAGE COMMUNICATION AND RETRIEVAL

NASA Technical Reports Server (NTRS)

Wall, R. J.

1994-01-01

VICAR (Video Image Communication and Retrieval) is a general purpose image processing software system that has been under continuous development since the late 1960's. Originally intended for data from the NASA Jet Propulsion Laboratory's unmanned planetary spacecraft, VICAR is now used for a variety of other applications including biomedical image processing, cartography, earth resources, and geological exploration. The development of this newest version of VICAR emphasized a standardized, easily-understood user interface, a shield between the user and the host operating system, and a comprehensive array of image processing capabilities. Structurally, VICAR can be divided into roughly two parts; a suite of applications programs and an executive which serves as the interfaces between the applications, the operating system, and the user. There are several hundred applications programs ranging in function from interactive image editing, data compression/decompression, and map projection, to blemish, noise, and artifact removal, mosaic generation, and pattern recognition and location. An information management system designed specifically for handling image related data can merge image data with other types of data files. The user accesses these programs through the VICAR executive, which consists of a supervisor and a run-time library. From the viewpoint of the user and the applications programs, the executive is an environment that is independent of the operating system. VICAR does not replace the host computer's operating system; instead, it overlays the host resources. The core of the executive is the VICAR Supervisor, which is based on NASA Goddard Space Flight Center's Transportable Applications Executive (TAE). Various modifications and extensions have been made to optimize TAE for image processing applications, resulting in a user friendly environment. The rest of the executive consists of the VICAR Run-Time Library, which provides a set of subroutines (image I/O, label I/O, parameter I/O, etc.) to facilitate image processing and provide the fastest I/O possible while maintaining a wide variety of capabilities. The run-time library also includes the Virtual Raster Display Interface (VRDI) which allows display oriented applications programs to be written for a variety of display devices using a set of common routines. (A display device can be any frame-buffer type device which is attached to the host computer and has memory planes for the display and manipulation of images. A display device may have any number of separate 8-bit image memory planes (IMPs), a graphics overlay plane, pseudo-color capabilities, hardware zoom and pan, and other features). The VRDI supports the following display devices: VICOM (Gould/Deanza) IP8500, RAMTEK RM-9465, ADAGE (Ikonas) IK3000 and the International Imaging Systems IVAS. VRDI's purpose is to provide a uniform operating environment not only for an application programmer, but for the user as well. The programmer is able to write programs without being concerned with the specifics of the device for which the application is intended. The VICAR Interactive Display Subsystem (VIDS) is a collection of utilities for easy interactive display and manipulation of images on a display device. VIDS has characteristics of both the executive and an application program, and offers a wide menu of image manipulation options. VIDS uses the VRDI to communicate with display devices. The first step in using VIDS to analyze and enhance an image (one simple example of VICAR's numerous capabilities) is to examine the histogram of the image. The histogram is a plot of frequency of occurrence for each pixel value (0 - 255) loaded in the image plane. If, for example, the histogram shows that there are no pixel values below 64 or above 192, the histogram can be "stretched" so that the value of 64 is mapped to zero and 192 is mapped to 255. Now the user can use the full dynamic range of the display device to display the data and better see its contents. Another example of a VIDS procedure is the JMOVIE command, which allows the user to run animations interactively on the display device. JMOVIE uses the concept of "frames", which are the individual frames which comprise the animation to be viewed. The user loads images into the frames after the size and number of frames has been selected. VICAR's source languages are primarily FORTRAN and C, with some VAX Assembler and array processor code. The VICAR run-time library is designed to work equally easily from either FORTRAN or C. The program was implemented on a DEC VAX series computer operating under VMS 4.7. The virtual memory required is 1.5MB. Approximately 180,000 blocks of storage are needed for the saveset. VICAR (version 2.3A/3G/13H) is a copyrighted work with all copyright vested in NASA and is available by license for a period of ten (10) years to approved licensees. This program was developed in 1989.

Application of histogram analysis for the evaluation of vascular permeability in glioma by the K2 parameter obtained with the dynamic susceptibility contrast method: Comparisons with Ktrans obtained with the dynamic contrast enhance method and cerebral blood volume.

PubMed

Taoka, Toshiaki; Kawai, Hisashi; Nakane, Toshiki; Hori, Saeka; Ochi, Tomoko; Miyasaka, Toshiteru; Sakamoto, Masahiko; Kichikawa, Kimihiko; Naganawa, Shinji

2016-09-01

The "K2" value is a factor that represents the vascular permeability of tumors and can be calculated from datasets obtained with the dynamic susceptibility contrast (DSC) method. The purpose of the current study was to correlate K2 with Ktrans, which is a well-established permeability parameter obtained with the dynamic contrast enhance (DCE) method, and determine the usefulness of K2 for glioma grading with histogram analysis. The subjects were 22 glioma patients (Grade II: 5, III: 6, IV: 11) who underwent DSC studies, including eight patients in which both DSC and DCE studies were performed on separate days within 10days. We performed histogram analysis of regions of interest of the tumors and acquired 20th percentile values for leakage-corrected cerebral blood volume (rCBV20%ile), K2 (K220%ile), and for patients who underwent a DCE study, Ktrans (Ktrans20%ile). We evaluated the correlation between K220%ile and Ktrans20%ile and the statistical difference between rCBV20%ile and K220%ile. We found a statistically significant correlation between K220%ile and Ktrans20%ile (r=0.717, p<0.05). rCBV20%ile showed a significant difference between Grades II and III and between Grades II and IV, whereas K220%ile showed a statistically significant (p<0.05) difference between Grades II and IV and between Grades III and IV. The K2 value calculated from the DSC dataset, which can be obtained with a short acquisition time, showed a correlation with Ktrans obtained with the DCE method and may be useful for glioma grading when analyzed with histogram analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Histogram analysis of apparent diffusion coefficient maps for the differentiation between lymphoma and metastatic lymph nodes of squamous cell carcinoma in head and neck region.

PubMed

Wang, Yan-Jun; Xu, Xiao-Quan; Hu, Hao; Su, Guo-Yi; Shen, Jie; Shi, Hai-Bin; Wu, Fei-Yun

2018-06-01

Background To clarify the nature of cervical malignant lymphadenopathy is highly important for the diagnosis and differential diagnosis of head and neck tumors. Purpose To investigate the role of first-order apparent diffusion coefficient (ADC) histogram analysis for differentiating lymphoma from metastatic lymph nodes of squamous cell carcinoma (SCC) in the head and neck region. Material and Methods Diffusion-weighted imaging (DWI) data of 67 patients (lymphoma, n = 20; SCC, n = 47) with malignant lymphadenopathy were retrospectively analyzed. The SCC group was divided into nasopharyngeal SCC and non-nasopharyngeal SCC groups. The ADC histogram features (ADC 10 , ADC 25 , ADC mean , ADC median , ADC 75 , ADC 90 , skewness, and kurtosis) were derived and then compared by independent-samples t-test and one-way analysis of variance test, respectively. Receiver operating characteristic curve analyses were employed to investigate diagnostic performance of the significant parameters. Results Lymphoma showed significantly lower ADC mean , ADC median , ADC 75 , and ADC 90 than SCC (all P < 0.05). Setting ADC 90  = 0.719 × 10 -3  mm 2 /s as the threshold value, optimal diagnostic performance was achieved (area under the curve [AUC] = 0.719, sensitivity = 95.7%, specificity = 50.0%). Subgroup analyses showed no significant difference between lymphoma and NPC (all P > 0.05). Lymphoma showed significantly lower ADC 25 , ADC mean , ADC median , ADC 75 , and ADC 90 than non-nasopharyngeal SCC (all P < 0.05). Optimal diagnostic performance (AUC = 0.847, sensitivity = 86.7%, specificity = 80.0%) could be achieved when setting ADC 90  = 0.943 × 10 -3  mm 2 /s as the threshold value. Conclusion Given its limitations, our study has shown that first-order ADC histogram analysis is capable of differentiating lymphoma from metastatic lymph nodes of SCC, especially those of non-nasopharyngeal SCC.

Histogram analysis of diffusion kurtosis imaging of nasopharyngeal carcinoma: Correlation between quantitative parameters and clinical stage.

PubMed

Xu, Xiao-Quan; Ma, Gao; Wang, Yan-Jun; Hu, Hao; Su, Guo-Yi; Shi, Hai-Bin; Wu, Fei-Yun

2017-07-18

To evaluate the correlation between histogram parameters derived from diffusion-kurtosis (DK) imaging and the clinical stage of nasopharyngeal carcinoma (NPC). High T-stage (T3/4) NPC showed significantly higher Kapp-mean (P = 0.018), Kapp-median (P = 0.029) and Kapp-90th (P = 0.003) than low T-stage (T1/2) NPC. High N-stage NPC (N2/3) showed significantly lower Dapp-mean (P = 0.002), Dapp-median (P = 0.002) and Dapp-10th (P < 0.001) than low N-stage NPC (N0/1). High AJCC-stage NPC (III/IV) showed significantly lower Dapp-10th (P = 0.038) than low AJCC-stage NPC (I/II). ROC analyses indicated that Kapp-90th was optimal for predicting high T-stage (AUC, 0.759; sensitivity, 0.842; specificity, 0.607), while Dapp-10th was best for predicting high N- and AJCC-stage (N-stage, AUC, 0.841; sensitivity, 0.875; specificity, 0.807; AJCC-stage, AUC, 0.671; sensitivity, 0.800; specificity, 0.588). DK imaging data of forty-seven consecutive NPC patients were retrospectively analyzed. Apparent diffusion for Gaussian distribution (Dapp) and apparent kurtosis coefficient (Kapp) were generated using diffusion-kurtosis model. Histogram parameters, including mean, median, 10th, 90th percentiles, skewness and kurtosis of Dapp and Kapp were calculated. Patients were divided into low and high T, N and clinical stage based on American Joint Committee on Cancer (AJCC) staging system. Differences of histogram parameters between low and high T, N and AJCC stages were compared using t test. Multiple receiver operating characteristic (ROC) curves were used to determine and compare the value of significant parameters in predicting high T, N and AJCC stage, respectively. DK imaging-derived parameters correlated well with clinical stage of NPC, therefore could serve as an adjunctive imaging technique for evaluating NPC.

Parameters of proteome evolution from histograms of amino-acid sequence identities of paralogous proteins

PubMed Central

Axelsen, Jacob Bock; Yan, Koon-Kiu; Maslov, Sergei

2007-01-01

Background The evolution of the full repertoire of proteins encoded in a given genome is mostly driven by gene duplications, deletions, and sequence modifications of existing proteins. Indirect information about relative rates and other intrinsic parameters of these three basic processes is contained in the proteome-wide distribution of sequence identities of pairs of paralogous proteins. Results We introduce a simple mathematical framework based on a stochastic birth-and-death model that allows one to extract some of this information and apply it to the set of all pairs of paralogous proteins in H. pylori, E. coli, S. cerevisiae, C. elegans, D. melanogaster, and H. sapiens. It was found that the histogram of sequence identities p generated by an all-to-all alignment of all protein sequences encoded in a genome is well fitted with a power-law form ~ p-γ with the value of the exponent γ around 4 for the majority of organisms used in this study. This implies that the intra-protein variability of substitution rates is best described by the Gamma-distribution with the exponent α ≈ 0.33. Different features of the shape of such histograms allow us to quantify the ratio between the genome-wide average deletion/duplication rates and the amino-acid substitution rate. Conclusion We separately measure the short-term ("raw") duplication and deletion rates rdup∗, rdel∗ which include gene copies that will be removed soon after the duplication event and their dramatically reduced long-term counterparts rdup, rdel. High deletion rate among recently duplicated proteins is consistent with a scenario in which they didn't have enough time to significantly change their functional roles and thus are to a large degree disposable. Systematic trends of each of the four duplication/deletion rates with the total number of genes in the genome were analyzed. All but the deletion rate of recent duplicates rdel∗ were shown to systematically increase with Ngenes. Abnormally flat shapes of sequence identity histograms observed for yeast and human are consistent with lineages leading to these organisms undergoing one or more whole-genome duplications. This interpretation is corroborated by our analysis of the genome of Paramecium tetraurelia where the p-4 profile of the histogram is gradually restored by the successive removal of paralogs generated in its four known whole-genome duplication events. PMID:18039386

Histogram analysis of apparent diffusion coefficient for monitoring early response in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy.

PubMed

Meng, Jie; Zhu, Lijing; Zhu, Li; Ge, Yun; He, Jian; Zhou, Zhengyang; Yang, Xiaofeng

2017-11-01

Background Apparent diffusion coefficient (ADC) histogram analysis has been widely used in determining tumor prognosis. Purpose To investigate the dynamic changes of ADC histogram parameters during concurrent chemo-radiotherapy (CCRT) in patients with advanced cervical cancers. Material and Methods This prospective study enrolled 32 patients with advanced cervical cancers undergoing CCRT who received diffusion-weighted (DW) magnetic resonance imaging (MRI) before CCRT, at the end of the second and fourth week during CCRT and one month after CCRT completion. The ADC histogram for the entire tumor volume was generated, and a series of histogram parameters was obtained. Dynamic changes of those parameters in cervical cancers were investigated as early biomarkers for treatment response. Results All histogram parameters except AUC low showed significant changes during CCRT (all P < 0.05). There were three variable trends involving different parameters. The mode, 5th, 10th, and 25th percentiles showed similar early increase rates (33.33%, 33.99%, 34.12%, and 30.49%, respectively) at the end of the second week of CCRT. The pre-CCRT 5th and 25th percentiles of the complete response (CR) group were significantly lower than those of the partial response (PR) group. Conclusion A series of ADC histogram parameters of cervical cancers changed significantly at the early stage of CCRT, indicating their potential in monitoring early tumor response to therapy.

Whole Tumor Histogram-profiling of Diffusion-Weighted Magnetic Resonance Images Reflects Tumorbiological Features of Primary Central Nervous System Lymphoma.

PubMed

Schob, Stefan; Münch, Benno; Dieckow, Julia; Quäschling, Ulf; Hoffmann, Karl-Titus; Richter, Cindy; Garnov, Nikita; Frydrychowicz, Clara; Krause, Matthias; Meyer, Hans-Jonas; Surov, Alexey

2018-04-01

Diffusion weighted imaging (DWI) quantifies motion of hydrogen nuclei in biological tissues and hereby has been used to assess the underlying tissue microarchitecture. Histogram-profiling of DWI provides more detailed information on diffusion characteristics of a lesion than the standardly calculated values of the apparent diffusion coefficient (ADC)-minimum, mean and maximum. Hence, the aim of our study was to investigate, which parameters of histogram-profiling of DWI in primary central nervous system lymphoma can be used to specifically predict features like cellular density, chromatin content and proliferative activity. Pre-treatment ADC maps of 21 PCNSL patients (8 female, 13 male, 28-89 years) from a 1.5T system were used for Matlab-based histogram profiling. Results of histopathology (H&E staining) and immunohistochemistry (Ki-67 expression) were quantified. Correlations between histogram-profiling parameters and neuropathologic examination were calculated using SPSS 23.0. The lower percentiles (p10 and p25) showed significant correlations with structural parameters of the neuropathologic examination (cellular density, chromatin content). The highest percentile, p90, correlated significantly with Ki-67 expression, resembling proliferative activity. Kurtosis of the ADC histogram correlated significantly with cellular density. Histogram-profiling of DWI in PCNSL provides a comprehensible set of parameters, which reflect distinct tumor-architectural and tumor-biological features, and hence, are promising biomarkers for treatment response and prognosis. Copyright © 2018. Published by Elsevier Inc.

Automatic detection method for mura defects on display film surface using modified Weber's law

NASA Astrophysics Data System (ADS)

Kim, Myung-Muk; Lee, Seung-Ho

2014-07-01

We propose a method that automatically detects mura defects on display film surfaces using a modified version of Weber's law. The proposed method detects mura defects regardless of their properties and shapes by identifying regions perceived by human vision as mura using the brightness of pixel and image distribution ratio of mura in an image histogram. The proposed detection method comprises five stages. In the first stage, the display film surface image is acquired and a gray-level shift performed. In the second and third stages, the image histogram is acquired and analyzed, respectively. In the fourth stage, the mura range is acquired. This is followed by postprocessing in the fifth stage. Evaluations of the proposed method conducted using 200 display film mura image samples indicate a maximum detection rate of ˜95.5%. Further, the results of application of the Semu index for luminance mura in flat panel display (FPD) image quality inspection indicate that the proposed method is more reliable than a popular conventional method.

Channel characterization and empirical model for ergodic capacity of free-space optical communication link

NASA Astrophysics Data System (ADS)

Alimi, Isiaka; Shahpari, Ali; Ribeiro, Vítor; Sousa, Artur; Monteiro, Paulo; Teixeira, António

2017-05-01

In this paper, we present experimental results on channel characterization of single input single output (SISO) free-space optical (FSO) communication link that is based on channel measurements. The histograms of the FSO channel samples and the log-normal distribution fittings are presented along with the measured scintillation index. Furthermore, we extend our studies to diversity schemes and propose a closed-form expression for determining ergodic channel capacity of multiple input multiple output (MIMO) FSO communication systems over atmospheric turbulence fading channels. The proposed empirical model is based on SISO FSO channel characterization. Also, the scintillation effects on the system performance are analyzed and results for different turbulence conditions are presented. Moreover, we observed that the histograms of the FSO channel samples that we collected from a 1548.51 nm link have good fits with log-normal distributions and the proposed model for MIMO FSO channel capacity is in conformity with the simulation results in terms of normalized mean-square error (NMSE).

Time-cumulated visible and infrared histograms used as descriptor of cloud cover

NASA Technical Reports Server (NTRS)

Seze, G.; Rossow, W.

1987-01-01

To study the statistical behavior of clouds for different climate regimes, the spatial and temporal stability of VIS-IR bidimensional histograms is tested. Also, the effect of data sampling and averaging on the histogram shapes is considered; in particular the sampling strategy used by the International Satellite Cloud Climatology Project is tested.

Interpreting Histograms. As Easy as It Seems?

ERIC Educational Resources Information Center

Lem, Stephanie; Onghena, Patrick; Verschaffel, Lieven; Van Dooren, Wim

2014-01-01

Histograms are widely used, but recent studies have shown that they are not as easy to interpret as it might seem. In this article, we report on three studies on the interpretation of histograms in which we investigated, namely, (1) whether the misinterpretation by university students can be considered to be the result of heuristic reasoning, (2)…

Improving Real World Performance of Vision Aided Navigation in a Flight Environment

DTIC Science & Technology

2016-09-15

Introduction . . . . . . . 63 4.2 Wide Area Search Extent . . . . . . . . . . . . . . . . . 64 4.3 Large-Scale Image Navigation Histogram Filter ...65 4.3.1 Location Model . . . . . . . . . . . . . . . . . . 66 4.3.2 Measurement Model . . . . . . . . . . . . . . . 66 4.3.3 Histogram Filter ...Iteration of Histogram Filter . . . . . . . . . . . 70 4.4 Implementation and Flight Test Campaign . . . . . . . . 71 4.4.1 Software Implementation

Airborne gamma-ray spectrometer and magnetometer survey, Durango A, Colorado. Final report Volume II A. Detail area

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

Not Available

1983-01-01

This volume contains geology of the Durango A detail area, radioactive mineral occurences in Colorado, and geophysical data interpretation. Eight appendices provide the following: stacked profiles, geologic histograms, geochemical histograms, speed and altitude histograms, geologic statistical tables, geochemical statistical tables, magnetic and ancillary profiles, and test line data.

Airborne gamma-ray spectrometer and magnetometer survey, Durango B, Colorado. Final report Volume II A. Detail area

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

Not Available

1983-01-01

The geology of the Durango B detail area, the radioactive mineral occurrences in Colorado and the geophysical data interpretation are included in this report. Seven appendices contain: stacked profiles, geologic histograms, geochemical histograms, speed and altitude histograms, geologic statistical tables, geochemical statistical tables, and test line data.

Students' Understanding of Bar Graphs and Histograms: Results from the LOCUS Assessments

ERIC Educational Resources Information Center

Whitaker, Douglas; Jacobbe, Tim

2017-01-01

Bar graphs and histograms are core statistical tools that are widely used in statistical practice and commonly taught in classrooms. Despite their importance and the instructional time devoted to them, many students demonstrate misunderstandings when asked to read and interpret bar graphs and histograms. Much of the research that has been…

Modeling Early Postnatal Brain Growth and Development with CT: Changes in the Brain Radiodensity Histogram from Birth to 2 Years.

PubMed

Cauley, K A; Hu, Y; Och, J; Yorks, P J; Fielden, S W

2018-04-01

The majority of brain growth and development occur in the first 2 years of life. This study investigated these changes by analysis of the brain radiodensity histogram of head CT scans from the clinical population, 0-2 years of age. One hundred twenty consecutive head CTs with normal findings meeting the inclusion criteria from children from birth to 2 years were retrospectively identified from 3 different CT scan platforms. Histogram analysis was performed on brain-extracted images, and histogram mean, mode, full width at half maximum, skewness, kurtosis, and SD were correlated with subject age. The effects of scan platform were investigated. Normative curves were fitted by polynomial regression analysis. Average total brain volume was 360 cm 3 at birth, 948 cm 3 at 1 year, and 1072 cm 3 at 2 years. Total brain tissue density showed an 11% increase in mean density at 1 year and 19% at 2 years. Brain radiodensity histogram skewness was positive at birth, declining logarithmically in the first 200 days of life. The histogram kurtosis also decreased in the first 200 days to approach a normal distribution. Direct segmentation of CT images showed that changes in brain radiodensity histogram skewness correlated with, and can be explained by, a relative increase in gray matter volume and an increase in gray and white matter tissue density that occurs during this period of brain maturation. Normative metrics of the brain radiodensity histogram derived from routine clinical head CT images can be used to develop a model of normal brain development. © 2018 by American Journal of Neuroradiology.

Histogram analysis derived from apparent diffusion coefficient (ADC) is more sensitive to reflect serological parameters in myositis than conventional ADC analysis.

PubMed

Meyer, Hans Jonas; Emmer, Alexander; Kornhuber, Malte; Surov, Alexey

2018-05-01

Diffusion-weighted imaging (DWI) has the potential of being able to reflect histopathology architecture. A novel imaging approach, namely histogram analysis, is used to further characterize tissues on MRI. The aim of this study was to correlate histogram parameters derived from apparent diffusion coefficient (ADC) maps with serological parameters in myositis. 16 patients with autoimmune myositis were included in this retrospective study. DWI was obtained on a 1.5 T scanner by using the b-values of 0 and 1000 s mm - 2 . Histogram analysis was performed as a whole muscle measurement by using a custom-made Matlab-based application. The following ADC histogram parameters were estimated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, and the following percentiles ADCp10, ADCp25, ADCp75, ADCp90, as well histogram parameters kurtosis, skewness, and entropy. In all patients, the blood sample was acquired within 3 days to the MRI. The following serological parameters were estimated: alanine aminotransferase, aspartate aminotransferase, creatine kinase, lactate dehydrogenase, C-reactive protein (CRP) and myoglobin. All patients were screened for Jo1-autobodies. Kurtosis correlated inversely with CRP (p = -0.55 and 0.03). Furthermore, ADCp10 and ADCp90 values tended to correlate with creatine kinase (p = -0.43, 0.11, and p = -0.42, = 0.12 respectively). In addition, ADCmean, p10, p25, median, mode, and entropy were different between Jo1-positive and Jo1-negative patients. ADC histogram parameters are sensitive for detection of muscle alterations in myositis patients. Advances in knowledge: This study identified that kurtosis derived from ADC maps is associated with CRP in myositis patients. Furthermore, several ADC histogram parameters are statistically different between Jo1-positive and Jo1-negative patients.

Can histogram analysis of MR images predict aggressiveness in pancreatic neuroendocrine tumors?

PubMed

De Robertis, Riccardo; Maris, Bogdan; Cardobi, Nicolò; Tinazzi Martini, Paolo; Gobbo, Stefano; Capelli, Paola; Ortolani, Silvia; Cingarlini, Sara; Paiella, Salvatore; Landoni, Luca; Butturini, Giovanni; Regi, Paolo; Scarpa, Aldo; Tortora, Giampaolo; D'Onofrio, Mirko

2018-06-01

To evaluate MRI derived whole-tumour histogram analysis parameters in predicting pancreatic neuroendocrine neoplasm (panNEN) grade and aggressiveness. Pre-operative MR of 42 consecutive patients with panNEN >1 cm were retrospectively analysed. T1-/T2-weighted images and ADC maps were analysed. Histogram-derived parameters were compared to histopathological features using the Mann-Whitney U test. Diagnostic accuracy was assessed by ROC-AUC analysis; sensitivity and specificity were assessed for each histogram parameter. ADC entropy was significantly higher in G2-3 tumours with ROC-AUC 0.757; sensitivity and specificity were 83.3 % (95 % CI: 61.2-94.5) and 61.1 % (95 % CI: 36.1-81.7). ADC kurtosis was higher in panNENs with vascular involvement, nodal and hepatic metastases (p= .008, .021 and .008; ROC-AUC= 0.820, 0.709 and 0.820); sensitivity and specificity were: 85.7/74.3 % (95 % CI: 42-99.2 /56.4-86.9), 36.8/96.5 % (95 % CI: 17.2-61.4 /76-99.8) and 100/62.8 % (95 % CI: 56.1-100/44.9-78.1). No significant differences between groups were found for other histogram-derived parameters (p >.05). Whole-tumour histogram analysis of ADC maps may be helpful in predicting tumour grade, vascular involvement, nodal and liver metastases in panNENs. ADC entropy and ADC kurtosis are the most accurate parameters for identification of panNENs with malignant behaviour. • Whole-tumour ADC histogram analysis can predict aggressiveness in pancreatic neuroendocrine neoplasms. • ADC entropy and kurtosis are higher in aggressive tumours. • ADC histogram analysis can quantify tumour diffusion heterogeneity. • Non-invasive quantification of tumour heterogeneity can provide adjunctive information for prognostication.

Non-small cell lung cancer: Whole-lesion histogram analysis of the apparent diffusion coefficient for assessment of tumor grade, lymphovascular invasion and pleural invasion.

PubMed

Tsuchiya, Naoko; Doai, Mariko; Usuda, Katsuo; Uramoto, Hidetaka; Tonami, Hisao

2017-01-01

Investigating the diagnostic accuracy of histogram analyses of apparent diffusion coefficient (ADC) values for determining non-small cell lung cancer (NSCLC) tumor grades, lymphovascular invasion, and pleural invasion. We studied 60 surgically diagnosed NSCLC patients. Diffusion-weighted imaging (DWI) was performed in the axial plane using a navigator-triggered single-shot, echo-planar imaging sequence with prospective acquisition correction. The ADC maps were generated, and we placed a volume-of-interest on the tumor to construct the whole-lesion histogram. Using the histogram, we calculated the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC, skewness, and kurtosis. Histogram parameters were correlated with tumor grade, lymphovascular invasion, and pleural invasion. We performed a receiver operating characteristics (ROC) analysis to assess the diagnostic performance of histogram parameters for distinguishing different pathologic features. The ADC mean, 10th, 25th, 50th, 75th, 90th, and 95th percentiles showed significant differences among the tumor grades. The ADC mean, 25th, 50th, 75th, 90th, and 95th percentiles were significant histogram parameters between high- and low-grade tumors. The ROC analysis between high- and low-grade tumors showed that the 95th percentile ADC achieved the highest area under curve (AUC) at 0.74. Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis. Kurtosis achieved the highest AUC at 0.809. Pleural invasion was only associated with skewness, with the AUC of 0.648. ADC histogram analyses on the basis of the entire tumor volume are able to stratify NSCLCs' tumor grade, lymphovascular invasion and pleural invasion.

Investigation on improved infrared image detail enhancement algorithm based on adaptive histogram statistical stretching and gradient filtering

NASA Astrophysics Data System (ADS)

Zeng, Bangze; Zhu, Youpan; Li, Zemin; Hu, Dechao; Luo, Lin; Zhao, Deli; Huang, Juan

2014-11-01

Duo to infrared image with low contrast, big noise and unclear visual effect, target is very difficult to observed and identified. This paper presents an improved infrared image detail enhancement algorithm based on adaptive histogram statistical stretching and gradient filtering (AHSS-GF). Based on the fact that the human eyes are very sensitive to the edges and lines, the author proposed to extract the details and textures by using the gradient filtering. New histogram could be acquired by calculating the sum of original histogram based on fixed window. With the minimum value for cut-off point, author carried on histogram statistical stretching. After the proper weights given to the details and background, the detail-enhanced results could be acquired finally. The results indicate image contrast could be improved and the details and textures could be enhanced effectively as well.

Dosimetric impact in the dose-volume histograms of rectal and vesical wall contouring in prostate cancer IMRT treatments.

PubMed

Gómez, Laura; Andrés, Carlos; Ruiz, Antonio

2017-01-01

The main purpose of this study was to evaluate the differences in dose-volume histograms of IMRT treatments for prostate cancer based on the delineation of the main organs at risk (rectum and bladder) as solid organs or by contouring their wall. Rectum and bladder have typically been delineated as solid organs, including the waste material, which, in practice, can lead to an erroneous assessment of the risk of adverse effects. A retrospective study was made on 25 patients treated with IMRT radiotherapy for prostate adenocarcinoma. 76.32 Gy in 36 fractions was prescribed to the prostate and seminal vesicles. In addition to the delineation of the rectum and bladder as solid organs (including their content), the rectal and bladder wall were also delineated and the resulting dose-volume histograms were analyzed for the two groups of structures. Data analysis shows statistically significant differences in the main parameters used to assess the risk of toxicity of a prostate radiotherapy treatment. Higher doses were received on the rectal and bladder walls compared to doses received on the corresponding solid organs. The observed differences in terms of received doses to the rectum and bladder based on the method of contouring could gain greater importance in inverse planning treatments, where the treatment planning system optimizes the dose in these volumes. So, one should take into account the method of delineating of these structures to make a clinical decision regarding dose limitation and risk assessment of chronic toxicity.

An Experimental Comparison of Similarity Assessment Measures for 3D Models on Constrained Surface Deformation

NASA Astrophysics Data System (ADS)

Quan, Lulin; Yang, Zhixin

2010-05-01

To address the issues in the area of design customization, this paper expressed the specification and application of the constrained surface deformation, and reported the experimental performance comparison of three prevail effective similarity assessment algorithms on constrained surface deformation domain. Constrained surface deformation becomes a promising method that supports for various downstream applications of customized design. Similarity assessment is regarded as the key technology for inspecting the success of new design via measuring the difference level between the deformed new design and the initial sample model, and indicating whether the difference level is within the limitation. According to our theoretical analysis and pre-experiments, three similarity assessment algorithms are suitable for this domain, including shape histogram based method, skeleton based method, and U system moment based method. We analyze their basic functions and implementation methodologies in detail, and do a series of experiments on various situations to test their accuracy and efficiency using precision-recall diagram. Shoe model is chosen as an industrial example for the experiments. It shows that shape histogram based method gained an optimal performance in comparison. Based on the result, we proposed a novel approach that integrating surface constrains and shape histogram description with adaptive weighting method, which emphasize the role of constrains during the assessment. The limited initial experimental result demonstrated that our algorithm outperforms other three algorithms. A clear direction for future development is also drawn at the end of the paper.

Accelerated weight histogram method for exploring free energy landscapes

NASA Astrophysics Data System (ADS)

Lindahl, V.; Lidmar, J.; Hess, B.

2014-07-01

Calculating free energies is an important and notoriously difficult task for molecular simulations. The rapid increase in computational power has made it possible to probe increasingly complex systems, yet extracting accurate free energies from these simulations remains a major challenge. Fully exploring the free energy landscape of, say, a biological macromolecule typically requires sampling large conformational changes and slow transitions. Often, the only feasible way to study such a system is to simulate it using an enhanced sampling method. The accelerated weight histogram (AWH) method is a new, efficient extended ensemble sampling technique which adaptively biases the simulation to promote exploration of the free energy landscape. The AWH method uses a probability weight histogram which allows for efficient free energy updates and results in an easy discretization procedure. A major advantage of the method is its general formulation, making it a powerful platform for developing further extensions and analyzing its relation to already existing methods. Here, we demonstrate its efficiency and general applicability by calculating the potential of mean force along a reaction coordinate for both a single dimension and multiple dimensions. We make use of a non-uniform, free energy dependent target distribution in reaction coordinate space so that computational efforts are not wasted on physically irrelevant regions. We present numerical results for molecular dynamics simulations of lithium acetate in solution and chignolin, a 10-residue long peptide that folds into a β-hairpin. We further present practical guidelines for setting up and running an AWH simulation.

Accelerated weight histogram method for exploring free energy landscapes.

PubMed

Lindahl, V; Lidmar, J; Hess, B

2014-07-28

Calculating free energies is an important and notoriously difficult task for molecular simulations. The rapid increase in computational power has made it possible to probe increasingly complex systems, yet extracting accurate free energies from these simulations remains a major challenge. Fully exploring the free energy landscape of, say, a biological macromolecule typically requires sampling large conformational changes and slow transitions. Often, the only feasible way to study such a system is to simulate it using an enhanced sampling method. The accelerated weight histogram (AWH) method is a new, efficient extended ensemble sampling technique which adaptively biases the simulation to promote exploration of the free energy landscape. The AWH method uses a probability weight histogram which allows for efficient free energy updates and results in an easy discretization procedure. A major advantage of the method is its general formulation, making it a powerful platform for developing further extensions and analyzing its relation to already existing methods. Here, we demonstrate its efficiency and general applicability by calculating the potential of mean force along a reaction coordinate for both a single dimension and multiple dimensions. We make use of a non-uniform, free energy dependent target distribution in reaction coordinate space so that computational efforts are not wasted on physically irrelevant regions. We present numerical results for molecular dynamics simulations of lithium acetate in solution and chignolin, a 10-residue long peptide that folds into a β-hairpin. We further present practical guidelines for setting up and running an AWH simulation.

Research of image retrieval technology based on color feature

NASA Astrophysics Data System (ADS)

Fu, Yanjun; Jiang, Guangyu; Chen, Fengying

2009-10-01

Recently, with the development of the communication and the computer technology and the improvement of the storage technology and the capability of the digital image equipment, more and more image resources are given to us than ever. And thus the solution of how to locate the proper image quickly and accurately is wanted.The early method is to set up a key word for searching in the database, but now the method has become very difficult when we search much more picture that we need. In order to overcome the limitation of the traditional searching method, content based image retrieval technology was aroused. Now, it is a hot research subject.Color image retrieval is the important part of it. Color is the most important feature for color image retrieval. Three key questions on how to make use of the color characteristic are discussed in the paper: the expression of color, the abstraction of color characteristic and the measurement of likeness based on color. On the basis, the extraction technology of the color histogram characteristic is especially discussed. Considering the advantages and disadvantages of the overall histogram and the partition histogram, a new method based the partition-overall histogram is proposed. The basic thought of it is to divide the image space according to a certain strategy, and then calculate color histogram of each block as the color feature of this block. Users choose the blocks that contain important space information, confirming the right value. The system calculates the distance between the corresponding blocks that users choosed. Other blocks merge into part overall histograms again, and the distance should be calculated. Then accumulate all the distance as the real distance between two pictures. The partition-overall histogram comprehensive utilizes advantages of two methods above, by choosing blocks makes the feature contain more spatial information which can improve performance; the distances between partition-overall histogram make rotating and translation does not change. The HSV color space is used to show color characteristic of image, which is suitable to the visual characteristic of human. Taking advance of human's feeling to color, it quantifies color sector with unequal interval, and get characteristic vector. Finally, it matches the similarity of image with the algorithm of the histogram intersection and the partition-overall histogram. Users can choose a demonstration image to show inquired vision require, and also can adjust several right value through the relevance-feedback method to obtain the best result of search.An image retrieval system based on these approaches is presented. The result of the experiments shows that the image retrieval based on partition-overall histogram can keep the space distribution information while abstracting color feature efficiently, and it is superior to the normal color histograms in precision rate while researching. The query precision rate is more than 95%. In addition, the efficient block expression will lower the complicate degree of the images to be searched, and thus the searching efficiency will be increased. The image retrieval algorithms based on the partition-overall histogram proposed in the paper is efficient and effective.

RF environment survey of Space Shuttle related EEE frequency bands

NASA Technical Reports Server (NTRS)

Simpson, J.; Prigel, B.; Postelle, J.

1977-01-01

Radio frequency assignments within the continental United States in frequency bands between 121 MHz abd 65 GHz were surveyed and analyzed in order to determine current utilization of anticipated frequency bands for the shuttle borne electromagnetic environment experiment. Data from both government and nongovernment files were used. Results are presented in both narrative form and in histograms which show the total number of unclassified assignments versus frequency and total assigned power versus frequency.

A histogram-based technique for rapid vector extraction from PIV photographs

NASA Technical Reports Server (NTRS)

Humphreys, William M., Jr.

1991-01-01

A new analysis technique, performed totally in the image plane, is proposed which rapidly extracts all available vectors from individual interrogation regions on PIV photographs. The technique avoids the need for using Fourier transforms with the associated computational burden. The data acquisition and analysis procedure is described, and results of a preliminary simulation study to evaluate the accuracy of the technique are presented. Recently obtained PIV photographs are analyzed.

Histogram analysis of greyscale sonograms to differentiate between the subtypes of follicular variant of papillary thyroid cancer.

PubMed

Kwon, M-R; Shin, J H; Hahn, S Y; Oh, Y L; Kwak, J Y; Lee, E; Lim, Y

2018-06-01

To evaluate the diagnostic value of histogram analysis using ultrasound (US) to differentiate between the subtypes of follicular variant of papillary thyroid carcinoma (FVPTC). The present study included 151 patients with surgically confirmed FVPTC diagnosed between January 2014 and May 2016. Their preoperative US features were reviewed retrospectively. Histogram parameters (mean, maximum, minimum, range, root mean square, skewness, kurtosis, energy, entropy, and correlation) were obtained for each nodule. The 152 nodules in 151 patients comprised 48 non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTPs; 31.6%), 60 invasive encapsulated FVPTCs (EFVPTCs; 39.5%), and 44 infiltrative FVPTCs (28.9%). The US features differed significantly between the subtypes of FVPTC. Discrimination was achieved between NIFTPs and infiltrative FVPTC, and between invasive EFVPTC and infiltrative FVPTC using histogram parameters; however, the parameters were not significantly different between NIFTP and invasive EFVPTC. It is feasible to use greyscale histogram analysis to differentiate between NIFTP and infiltrative FVPTC, but not between NIFTP and invasive EFVPTC. Histograms can be used as a supplementary tool to differentiate the subtypes of FVPTC. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

DSP+FPGA-based real-time histogram equalization system of infrared image

NASA Astrophysics Data System (ADS)

Gu, Dongsheng; Yang, Nansheng; Pi, Defu; Hua, Min; Shen, Xiaoyan; Zhang, Ruolan

2001-10-01

Histogram Modification is a simple but effective method to enhance an infrared image. There are several methods to equalize an infrared image's histogram due to the different characteristics of the different infrared images, such as the traditional HE (Histogram Equalization) method, and the improved HP (Histogram Projection) and PE (Plateau Equalization) method and so on. If to realize these methods in a single system, the system must have a mass of memory and extremely fast speed. In our system, we introduce a DSP + FPGA based real-time procession technology to do these things together. FPGA is used to realize the common part of these methods while DSP is to do the different part. The choice of methods and the parameter can be input by a keyboard or a computer. By this means, the function of the system is powerful while it is easy to operate and maintain. In this article, we give out the diagram of the system and the soft flow chart of the methods. And at the end of it, we give out the infrared image and its histogram before and after the process of HE method.

True progression versus pseudoprogression in the treatment of glioblastomas: a comparison study of normalized cerebral blood volume and apparent diffusion coefficient by histogram analysis.

PubMed

Song, Yong Sub; Choi, Seung Hong; Park, Chul-Kee; Yi, Kyung Sik; Lee, Woong Jae; Yun, Tae Jin; Kim, Tae Min; Lee, Se-Hoon; Kim, Ji-Hoon; Sohn, Chul-Ho; Park, Sung-Hye; Kim, Il Han; Jahng, Geon-Ho; Chang, Kee-Hyun

2013-01-01

The purpose of this study was to differentiate true progression from pseudoprogression of glioblastomas treated with concurrent chemoradiotherapy (CCRT) with temozolomide (TMZ) by using histogram analysis of apparent diffusion coefficient (ADC) and normalized cerebral blood volume (nCBV) maps. Twenty patients with histopathologically proven glioblastoma who had received CCRT with TMZ underwent perfusion-weighted imaging and diffusion-weighted imaging (b = 0, 1000 sec/mm(2)). The corresponding nCBV and ADC maps for the newly visible, entirely enhancing lesions were calculated after the completion of CCRT with TMZ. Two observers independently measured the histogram parameters of the nCBV and ADC maps. The histogram parameters between the true progression group (n = 10) and the pseudoprogression group (n = 10) were compared by use of an unpaired Student's t test and subsequent multivariable stepwise logistic regression analysis to determine the best predictors for the differential diagnosis between the two groups. Receiver operating characteristic analysis was employed to determine the best cutoff values for the histogram parameters that proved to be significant predictors for differentiating true progression from pseudoprogression. Intraclass correlation coefficient was used to determine the level of inter-observer reliability for the histogram parameters. The 5th percentile value (C5) of the cumulative ADC histograms was a significant predictor for the differential diagnosis between true progression and pseudoprogression (p = 0.044 for observer 1; p = 0.011 for observer 2). Optimal cutoff values of 892 × 10(-6) mm(2)/sec for observer 1 and 907 × 10(-6) mm(2)/sec for observer 2 could help differentiate between the two groups with a sensitivity of 90% and 80%, respectively, a specificity of 90% and 80%, respectively, and an area under the curve of 0.880 and 0.840, respectively. There was no other significant differentiating parameter on the nCBV histograms. Inter-observer reliability was excellent or good for all histogram parameters (intraclass correlation coefficient range: 0.70-0.99). The C5 of the cumulative ADC histogram can be a promising parameter for the differentiation of true progression from pseudoprogression of newly visible, entirely enhancing lesions after CCRT with TMZ for glioblastomas.

True Progression versus Pseudoprogression in the Treatment of Glioblastomas: A Comparison Study of Normalized Cerebral Blood Volume and Apparent Diffusion Coefficient by Histogram Analysis

PubMed Central

Song, Yong Sub; Park, Chul-Kee; Yi, Kyung Sik; Lee, Woong Jae; Yun, Tae Jin; Kim, Tae Min; Lee, Se-Hoon; Kim, Ji-Hoon; Sohn, Chul-Ho; Park, Sung-Hye; Kim, Il Han; Jahng, Geon-Ho; Chang, Kee-Hyun

2013-01-01

Objective The purpose of this study was to differentiate true progression from pseudoprogression of glioblastomas treated with concurrent chemoradiotherapy (CCRT) with temozolomide (TMZ) by using histogram analysis of apparent diffusion coefficient (ADC) and normalized cerebral blood volume (nCBV) maps. Materials and Methods Twenty patients with histopathologically proven glioblastoma who had received CCRT with TMZ underwent perfusion-weighted imaging and diffusion-weighted imaging (b = 0, 1000 sec/mm2). The corresponding nCBV and ADC maps for the newly visible, entirely enhancing lesions were calculated after the completion of CCRT with TMZ. Two observers independently measured the histogram parameters of the nCBV and ADC maps. The histogram parameters between the true progression group (n = 10) and the pseudoprogression group (n = 10) were compared by use of an unpaired Student's t test and subsequent multivariable stepwise logistic regression analysis to determine the best predictors for the differential diagnosis between the two groups. Receiver operating characteristic analysis was employed to determine the best cutoff values for the histogram parameters that proved to be significant predictors for differentiating true progression from pseudoprogression. Intraclass correlation coefficient was used to determine the level of inter-observer reliability for the histogram parameters. Results The 5th percentile value (C5) of the cumulative ADC histograms was a significant predictor for the differential diagnosis between true progression and pseudoprogression (p = 0.044 for observer 1; p = 0.011 for observer 2). Optimal cutoff values of 892 × 10-6 mm2/sec for observer 1 and 907 × 10-6 mm2/sec for observer 2 could help differentiate between the two groups with a sensitivity of 90% and 80%, respectively, a specificity of 90% and 80%, respectively, and an area under the curve of 0.880 and 0.840, respectively. There was no other significant differentiating parameter on the nCBV histograms. Inter-observer reliability was excellent or good for all histogram parameters (intraclass correlation coefficient range: 0.70-0.99). Conclusion The C5 of the cumulative ADC histogram can be a promising parameter for the differentiation of true progression from pseudoprogression of newly visible, entirely enhancing lesions after CCRT with TMZ for glioblastomas. PMID:23901325

Variability in the microcanonical cascades parameters among gauges of urban precipitation monitoring network

NASA Astrophysics Data System (ADS)

Licznar, Paweł; Rupp, David; Adamowski, Witold

2013-04-01

In the fall of 2008, Municipal Water Supply and Sewerage Company (MWSSC) in Warsaw began operating the first large precipitation monitoring network dedicated to urban hydrology in Poland. The process of establishing the network as well as the preliminary phase of its operation, raised a number of questions concerning optimal gauge location and density and revealed the urgent need for new data processing techniques. When considering the full-field precipitation as input to hydrodynamic models of stormwater and combined sewage systems, standard processing techniques developed previously for single gauges and concentrating mainly on the analysis of maximum rainfall rates and intensity-duration-frequency (IDF) curves development were found inadequate. We used a multifractal rainfall modeling framework based on microcanonical multiplicative random cascades to analyze properties of Warsaw precipitation. We calculated breakdown coefficients (BDC) for the hierarchy of timescales from λ=1 (5-min) up to λ=128 (1280-min) for all 25 gauges in the network. At small timescales histograms of BDCs were strongly deformed due to the recording precision of rainfall amounts. A randomization procedure statistically removed the artifacts due to precision errors in the original series. At large timescales BDC values were sparse due to relatively short period of observations (2008-2011). An algorithm with a moving window was proposed to increase the number of BDC values at large timescales and to smooth their histograms. The resulting empirical BDC histograms were modeled by a theoretical "2N-B" distribution, which combined 2 separate normal (N) distributions and one beta (B) distribution. A clear evolution of BDC histograms from a 2N-B distribution for small timescales to a N-B distributions for intermediate timescales and finally to a single beta distributions for large timescales was observed for all gauges. Cluster analysis revealed close patterns of BDC distributions among almost all gauges and timescales with exception of two gauges located at the city limits (one gauge was located on the Okęcie airport). We evaluated the performance of the microcanonical cascades at disaggregating 1280-min (quasi daily precipitation totals) into 5-min rainfall data for selected gauges. Synthetic time series were analyzed with respect to their intermittency and variability of rainfall intensities and compared to observational series. We showed that microcanonical cascades models could be used in practice for generating synthetic rainfall time series suitable as input to urban hydrology models in Warsaw.

Assessment of Current Inservice Inspection and Leak Monitoring Practices for Detecting Materials Degradation in Light Water Reactors

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

Anderson, Michael T.; Simonen, Fredric A.; Muscara, Joseph

2016-09-01

An assessment was performed to determine the effectiveness of existing inservice inspection (ISI) and leak monitoring techniques, and recommend improvements, as necessary, to the programs as currently performed for light water reactor (LWR) components. Information from nuclear power plant (NPP) aging studies and from the U. S. Nuclear Regulatory Commission’s Generic Aging Lessons Learned (GALL) report (NUREG-1801) was used to identify components that have already experienced, or are expected to experience, degradation. This report provides a discussion of the key aspects and parameters that constitute an effective ISI program and a discussion of the basis and background against which themore » effectiveness of the ISI and leak monitoring programs for timely detection of degradation was evaluated. Tables based on the GALL components were used to systematically guide the process, and table columns were included that contained the ISI requirements and effectiveness assessment. The information in the tables was analyzed using histograms to reduce the data and help identify any trends. The analysis shows that the overall effectiveness of the ISI programs is very similar for both boiling water reactors (BWRs) and pressurized water reactors (PWRs). The evaluations conducted as part of this research showed that many ISI programs are not effective at detecting degradation before its extent reached 75% of the component wall thickness. This work should be considered as an assessment of NDE practices at this time; however, industry and regulatory activities are currently underway that will impact future effectiveness assessments. A number of actions have been identified to improve the current ISI programs so that degradation can be more reliably detected.« less

[Development of a Compared Software for Automatically Generated DVH in Eclipse TPS].

PubMed

Xie, Zhao; Luo, Kelin; Zou, Lian; Hu, Jinyou

2016-03-01

This study is to automatically calculate the dose volume histogram(DVH) for the treatment plan, then to compare it with requirements of doctor's prescriptions. The scripting language Autohotkey and programming language C# were used to develop a compared software for automatically generated DVH in Eclipse TPS. This software is named Show Dose Volume Histogram (ShowDVH), which is composed of prescription documents generation, operation functions of DVH, software visualization and DVH compared report generation. Ten cases in different cancers have been separately selected, in Eclipse TPS 11.0 ShowDVH could not only automatically generate DVH reports but also accurately determine whether treatment plans meet the requirements of doctor’s prescriptions, then reports gave direction for setting optimization parameters of intensity modulated radiated therapy. The ShowDVH is an user-friendly and powerful software, and can automatically generated compared DVH reports fast in Eclipse TPS 11.0. With the help of ShowDVH, it greatly saves plan designing time and improves working efficiency of radiation therapy physicists.

Fast and efficient search for MPEG-4 video using adjacent pixel intensity difference quantization histogram feature

NASA Astrophysics Data System (ADS)

Lee, Feifei; Kotani, Koji; Chen, Qiu; Ohmi, Tadahiro

2010-02-01

In this paper, a fast search algorithm for MPEG-4 video clips from video database is proposed. An adjacent pixel intensity difference quantization (APIDQ) histogram is utilized as the feature vector of VOP (video object plane), which had been reliably applied to human face recognition previously. Instead of fully decompressed video sequence, partially decoded data, namely DC sequence of the video object are extracted from the video sequence. Combined with active search, a temporal pruning algorithm, fast and robust video search can be realized. The proposed search algorithm has been evaluated by total 15 hours of video contained of TV programs such as drama, talk, news, etc. to search for given 200 MPEG-4 video clips which each length is 15 seconds. Experimental results show the proposed algorithm can detect the similar video clip in merely 80ms, and Equal Error Rate (ERR) of 2 % in drama and news categories are achieved, which are more accurately and robust than conventional fast video search algorithm.

MEKS: A program for computation of inclusive jet cross sections at hadron colliders

NASA Astrophysics Data System (ADS)

Gao, Jun; Liang, Zhihua; Soper, Davison E.; Lai, Hung-Liang; Nadolsky, Pavel M.; Yuan, C.-P.

2013-06-01

EKS is a numerical program that predicts differential cross sections for production of single-inclusive hadronic jets and jet pairs at next-to-leading order (NLO) accuracy in a perturbative QCD calculation. We describe MEKS 1.0, an upgraded EKS program with increased numerical precision, suitable for comparisons to the latest experimental data from the Large Hadron Collider and Tevatron. The program integrates the regularized patron-level matrix elements over the kinematical phase space for production of two and three partons using the VEGAS algorithm. It stores the generated weighted events in finely binned two-dimensional histograms for fast offline analysis. A user interface allows one to customize computation of inclusive jet observables. Results of a benchmark comparison of the MEKS program and the commonly used FastNLO program are also documented. Program SummaryProgram title: MEKS 1.0 Catalogue identifier: AEOX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland. Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 9234 No. of bytes in distributed program, including test data, etc.: 51997 Distribution format: tar.gz Programming language: Fortran (main program), C (CUBA library and analysis program). Computer: All. Operating system: Any UNIX-like system. RAM: ˜300 MB Classification: 11.1. External routines: LHAPDF (https://lhapdf.hepforge.org/) Nature of problem: Computation of differential cross sections for inclusive production of single hadronic jets and jet pairs at next-to-leading order accuracy in perturbative quantum chromodynamics. Solution method: Upon subtraction of infrared singularities, the hard-scattering matrix elements are integrated over available phase space using an optimized VEGAS algorithm. Weighted events are generated and filled into a finely binned two-dimensional histogram, from which the final cross sections with typical experimental binning and cuts are computed by an independent analysis program. Monte Carlo sampling of event weights is tuned automatically to get better efficiency. Running time: Depends on details of the calculation and sought numerical accuracy. See benchmark performance in Section 4. The tests provided take approximately 27 min for the jetbin run and a few seconds for jetana.

Histogram-based normalization technique on human brain magnetic resonance images from different acquisitions.

PubMed

Sun, Xiaofei; Shi, Lin; Luo, Yishan; Yang, Wei; Li, Hongpeng; Liang, Peipeng; Li, Kuncheng; Mok, Vincent C T; Chu, Winnie C W; Wang, Defeng

2015-07-28

Intensity normalization is an important preprocessing step in brain magnetic resonance image (MRI) analysis. During MR image acquisition, different scanners or parameters would be used for scanning different subjects or the same subject at a different time, which may result in large intensity variations. This intensity variation will greatly undermine the performance of subsequent MRI processing and population analysis, such as image registration, segmentation, and tissue volume measurement. In this work, we proposed a new histogram normalization method to reduce the intensity variation between MRIs obtained from different acquisitions. In our experiment, we scanned each subject twice on two different scanners using different imaging parameters. With noise estimation, the image with lower noise level was determined and treated as the high-quality reference image. Then the histogram of the low-quality image was normalized to the histogram of the high-quality image. The normalization algorithm includes two main steps: (1) intensity scaling (IS), where, for the high-quality reference image, the intensities of the image are first rescaled to a range between the low intensity region (LIR) value and the high intensity region (HIR) value; and (2) histogram normalization (HN),where the histogram of low-quality image as input image is stretched to match the histogram of the reference image, so that the intensity range in the normalized image will also lie between LIR and HIR. We performed three sets of experiments to evaluate the proposed method, i.e., image registration, segmentation, and tissue volume measurement, and compared this with the existing intensity normalization method. It is then possible to validate that our histogram normalization framework can achieve better results in all the experiments. It is also demonstrated that the brain template with normalization preprocessing is of higher quality than the template with no normalization processing. We have proposed a histogram-based MRI intensity normalization method. The method can normalize scans which were acquired on different MRI units. We have validated that the method can greatly improve the image analysis performance. Furthermore, it is demonstrated that with the help of our normalization method, we can create a higher quality Chinese brain template.

The number distribution of weak Explosive Events observed by SUMER/SoHO

NASA Astrophysics Data System (ADS)

Mendoza-Torres, J. E.

2016-11-01

Explosive Events (EEs) observed by SUMER on SoHO at the 1393.8 Å Si IV line are analyzed. We look for EEs to study their number distribution at low energies. Eight data sets taken in June 1996 in raster observations are used. In these observations a field on the solar disk is scanned several times during a period considerably longer than the typical timelife of an EE. To look for EE, we first identified the maxima and locations of spectral line increases. The maxima that took place at inner locations of the rastered fields were considered as possible EEs. From this sample, the cases where the spectral line underwent Doppler shifts at most ±3″ from the location of the maximum were considered EEs. After a selection, the region within 5″ of the event was ignored for 5 min either side of the EE in order to conclusively select a different maxima. Based on the analysis of the locations of EEs, it was seen that the more intense EEs tend to take place at given regions while at the intermediate regions the observed EEs are less intense. Therefore we refer to them as Regions of Enhanced Emission (REE) and Quiet Regions (QR), respectively. The width of the REE regions, as seen in North-South direction is about 10-30″. In this work, a total of 487 EEs are analyzed, 266 at REE and 221 at QR. Also, Histograms are made of the maxima of the amplitude of the spectral line during EEs at both REE and QR. At the Histogram for EEs at QR the number grows as the flux decreases with a slope of -1.8. For EEs at REE the Histogram has a maximum about 1 Watts m-2 sr-1 Å-1 with a high energy slope of about -1.6. These numbers are both below the value required to give an important input of energy for coronal heating, as analyzed in the case of microflares (Hudson, 1991). The averages of the maxima of EEs at each set for the REE and QR are computed. The scatter plot of the average values indicates that there is a linear relation between them and the maximum amplitudes of EEs at REE are about two times larger than the amplitudes for EEs at QR.

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

PubMed Central

2017-01-01

This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image. PMID:29403529

An Analysis of Measures Used to Evaluate the Air Force Critical Item Program

DTIC Science & Technology

1991-09-01

example of a histogram. Cause & Effect Diagram. The cause and effect diagram was introduced in 1953 by Dr. Kaoru Ishikawa in summarizing the opinions of...Personal Interview. Air Force Institute of Technology, School of Engineering, Wright-Patterson AFB OH, 24 April 1991. 31. Ishikawa , Dr. Kaoru . Guide to...collected. How the data are collected will determine which measurement techniques are appropriate. Ishikawa classifies data collection into five categories

Image contrast enhancement using adjacent-blocks-based modification for local histogram equalization

NASA Astrophysics Data System (ADS)

Wang, Yang; Pan, Zhibin

2017-11-01

Infrared images usually have some non-ideal characteristics such as weak target-to-background contrast and strong noise. Because of these characteristics, it is necessary to apply the contrast enhancement algorithm to improve the visual quality of infrared images. Histogram equalization (HE) algorithm is a widely used contrast enhancement algorithm due to its effectiveness and simple implementation. But a drawback of HE algorithm is that the local contrast of an image cannot be equally enhanced. Local histogram equalization algorithms are proved to be the effective techniques for local image contrast enhancement. However, over-enhancement of noise and artifacts can be easily found in the local histogram equalization enhanced images. In this paper, a new contrast enhancement technique based on local histogram equalization algorithm is proposed to overcome the drawbacks mentioned above. The input images are segmented into three kinds of overlapped sub-blocks using the gradients of them. To overcome the over-enhancement effect, the histograms of these sub-blocks are then modified by adjacent sub-blocks. We pay more attention to improve the contrast of detail information while the brightness of the flat region in these sub-blocks is well preserved. It will be shown that the proposed algorithm outperforms other related algorithms by enhancing the local contrast without introducing over-enhancement effects and additional noise.

Value of MR histogram analyses for prediction of microvascular invasion of hepatocellular carcinoma.

PubMed

Huang, Ya-Qin; Liang, He-Yue; Yang, Zhao-Xia; Ding, Ying; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-06-01

The objective is to explore the value of preoperative magnetic resonance (MR) histogram analyses in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC).Fifty-one patients with histologically confirmed HCC who underwent diffusion-weighted and contrast-enhanced MR imaging were included. Histogram analyses were performed and mean, variance, skewness, kurtosis, 1th, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared between HCCs with and without MVI. Receiver operating characteristics (ROC) analyses were generated to compare the diagnostic performance of tumor size, histogram analyses of apparent diffusion coefficient (ADC) maps, and MR enhancement.The mean, 1th, 10th, and 50th percentiles of ADC maps, and the mean, variance. 1th, 10th, 50th, 90th, and 99th percentiles of the portal venous phase (PVP) images were significantly different between the groups with and without MVI (P <0.05), with area under the ROC curves (AUCs) of 0.66 to 0.74 for ADC and 0.76 to 0.88 for PVP. The largest AUC of PVP (1th percentile) showed significantly higher accuracy compared with that of arterial phase (AP) or tumor size (P <0.001).MR histogram analyses-in particular for 1th percentile for PVP images-held promise for prediction of MVI of HCC.

Histogram analysis of apparent diffusion coefficient maps for differentiating primary CNS lymphomas from tumefactive demyelinating lesions.

PubMed

Lu, Shan Shan; Kim, Sang Joon; Kim, Namkug; Kim, Ho Sung; Choi, Choong Gon; Lim, Young Min

2015-04-01

This study intended to investigate the usefulness of histogram analysis of apparent diffusion coefficient (ADC) maps for discriminating primary CNS lymphomas (PCNSLs), especially atypical PCNSLs, from tumefactive demyelinating lesions (TDLs). Forty-seven patients with PCNSLs and 18 with TDLs were enrolled in our study. Hyperintense lesions seen on T2-weighted images were defined as ROIs after ADC maps were registered to the corresponding T2-weighted image. ADC histograms were calculated from the ROIs containing the entire lesion on every section and on a voxel-by-voxel basis. The ADC histogram parameters were compared among all PCNSLs and TDLs as well as between the subgroup of atypical PCNSLs and TDLs. ROC curves were constructed to evaluate the diagnostic performance of the histogram parameters and to determine the optimum thresholds. The differences between the PCNSLs and TDLs were found in the minimum ADC values (ADCmin) and in the 5th and 10th percentiles (ADC5% and ADC10%) of the cumulative ADC histograms. However, no statistical significance was found in the mean ADC value or in the ADC value concerning the mode, kurtosis, and skewness. The ADCmin, ADC5%, and ADC10% were also lower in atypical PCNSLs than in TDLs. ADCmin was the best indicator for discriminating atypical PCNSLs from TDLs, with a threshold of 556×10(-6) mm2/s (sensitivity, 81.3 %; specificity, 88.9%). Histogram analysis of ADC maps may help to discriminate PCNSLs from TDLs and may be particularly useful in differentiating atypical PCNSLs from TDLs.

Assessment of histological differentiation in gastric cancers using whole-volume histogram analysis of apparent diffusion coefficient maps.

PubMed

Zhang, Yujuan; Chen, Jun; Liu, Song; Shi, Hua; Guan, Wenxian; Ji, Changfeng; Guo, Tingting; Zheng, Huanhuan; Guan, Yue; Ge, Yun; He, Jian; Zhou, Zhengyang; Yang, Xiaofeng; Liu, Tian

2017-02-01

To investigate the efficacy of histogram analysis of the entire tumor volume in apparent diffusion coefficient (ADC) maps for differentiating between histological grades in gastric cancer. Seventy-eight patients with gastric cancer were enrolled in a retrospective 3.0T magnetic resonance imaging (MRI) study. ADC maps were obtained at two different b values (0 and 1000 sec/mm 2 ) for each patient. Tumors were delineated on each slice of the ADC maps, and a histogram for the entire tumor volume was subsequently generated. A series of histogram parameters (eg, skew and kurtosis) were calculated and correlated with the histological grade of the surgical specimen. The diagnostic performance of each parameter for distinguishing poorly from moderately well-differentiated gastric cancers was assessed by using the area under the receiver operating characteristic curve (AUC). There were significant differences in the 5 th , 10 th , 25 th , and 50 th percentiles, skew, and kurtosis between poorly and well-differentiated gastric cancers (P < 0.05). There were correlations between the degrees of differentiation and histogram parameters, including the 10 th percentile, skew, kurtosis, and max frequency; the correlation coefficients were 0.273, -0.361, -0.339, and -0.370, respectively. Among all the histogram parameters, the max frequency had the largest AUC value, which was 0.675. Histogram analysis of the ADC maps on the basis of the entire tumor volume can be useful in differentiating between histological grades for gastric cancer. 4 J. Magn. Reson. Imaging 2017;45:440-449. © 2016 International Society for Magnetic Resonance in Medicine.

Macronuclear chromatin structure dynamics in Colpoda inflata (Protista, Ciliophora) resting encystment.

PubMed

Tiano, L; Chessa, M G; Carrara, S; Tagliafierro, G; Delmonte Corrado, M U

1999-01-01

The chromatin structure dynamics of the Colpoda inflata macronucleus have been investigated in relation to its functional condition, concerning chromatin body extrusion regulating activity. Samples of 2- and 25-day-old resting cysts derived from a standard culture, and of 1-year-old resting cysts derived from a senescent culture, were examined by means of histogram analysis performed on acquired optical microscopy images. Three groups of histograms were detected in each sample. Histogram classification, clustering and matching were assessed in order to obtain the mean histogram of each group. Comparative analysis of the mean histogram showed a similarity in the grey level range of 25-day- and 1-year-old cysts, unlike the wider grey level range found in 2-day-old cysts. Moreover, the respective mean histograms of the three cyst samples appeared rather similar in shape. All this implies that macronuclear chromatin structural features of 1-year-old cysts are common to both cyst standard cultures. The evaluation of the acquired images and their respective histograms evidenced a dynamic state of the macronuclear chromatin, appearing differently condensed in relation to the chromatin body extrusion regulating activity of the macronucleus. The coexistence of a chromatin-decondensed macronucleus with a pycnotic extrusion body suggests that chromatin unable to decondense, thus inactive, is extruded. This finding, along with the presence of chromatin structural features common to standard and senescent cyst populations, supports the occurrence of 'rejuvenated' cell lines from 1-year-old encysted senescent cells, a phenomenon which could be a result of accomplished macronuclear renewal.

Non-small cell lung cancer: Whole-lesion histogram analysis of the apparent diffusion coefficient for assessment of tumor grade, lymphovascular invasion and pleural invasion

PubMed Central

Tsuchiya, Naoko; Doai, Mariko; Usuda, Katsuo; Uramoto, Hidetaka

2017-01-01

Purpose Investigating the diagnostic accuracy of histogram analyses of apparent diffusion coefficient (ADC) values for determining non-small cell lung cancer (NSCLC) tumor grades, lymphovascular invasion, and pleural invasion. Materials and methods We studied 60 surgically diagnosed NSCLC patients. Diffusion-weighted imaging (DWI) was performed in the axial plane using a navigator-triggered single-shot, echo-planar imaging sequence with prospective acquisition correction. The ADC maps were generated, and we placed a volume-of-interest on the tumor to construct the whole-lesion histogram. Using the histogram, we calculated the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC, skewness, and kurtosis. Histogram parameters were correlated with tumor grade, lymphovascular invasion, and pleural invasion. We performed a receiver operating characteristics (ROC) analysis to assess the diagnostic performance of histogram parameters for distinguishing different pathologic features. Results The ADC mean, 10th, 25th, 50th, 75th, 90th, and 95th percentiles showed significant differences among the tumor grades. The ADC mean, 25th, 50th, 75th, 90th, and 95th percentiles were significant histogram parameters between high- and low-grade tumors. The ROC analysis between high- and low-grade tumors showed that the 95th percentile ADC achieved the highest area under curve (AUC) at 0.74. Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis. Kurtosis achieved the highest AUC at 0.809. Pleural invasion was only associated with skewness, with the AUC of 0.648. Conclusions ADC histogram analyses on the basis of the entire tumor volume are able to stratify NSCLCs' tumor grade, lymphovascular invasion and pleural invasion. PMID:28207858

The use of thematic mapper data for land cover discrimination: Preliminary results from the UK SATMaP programme

NASA Technical Reports Server (NTRS)

Jackson, M. J.; Baker, J. R.; Townshend, J. R. G.; Gayler, J. E.; Hardy, J. R.

1983-01-01

The principal objectives of the UK SATMaP program are to determine thematic mapper (TM) performance with particular reference to spatial resolution properties and geometric characteristics of the data. So far, analysis is restricted to images from the U.S. and concentrates on spectra and radiometric properties. The results indicate that the data are inherently three dimensional compared with the two dimensional character of MSS data. Preliminary classification results indicate the importance of the near infrared band (TM 4), at least one middle infrared band (TM 5 or TM 6) and at least one of the visible bands (preferably either TM 3 or TM 1). The thermal infrared also appears to have discriminatory ability despite its coarser spatial resolution. For band 4 the forward and reverse scans show somewhat different spectral responses in one scene but this effect is absent in the other analyzed. From examination of the histograms it would appear that the full 8-bit quantization is not being effectively utilized for all the bands.

A psychophysical comparison of two methods for adaptive histogram equalization.

PubMed

Zimmerman, J B; Cousins, S B; Hartzell, K M; Frisse, M E; Kahn, M G

1989-05-01

Adaptive histogram equalization (AHE) is a method for adaptive contrast enhancement of digital images. It is an automatic, reproducible method for the simultaneous viewing of contrast within a digital image with a large dynamic range. Recent experiments have shown that in specific cases, there is no significant difference in the ability of AHE and linear intensity windowing to display gray-scale contrast. More recently, a variant of AHE which limits the allowed contrast enhancement of the image has been proposed. This contrast-limited adaptive histogram equalization (CLAHE) produces images in which the noise content of an image is not excessively enhanced, but in which sufficient contrast is provided for the visualization of structures within the image. Images processed with CLAHE have a more natural appearance and facilitate the comparison of different areas of an image. However, the reduced contrast enhancement of CLAHE may hinder the ability of an observer to detect the presence of some significant gray-scale contrast. In this report, a psychophysical observer experiment was performed to determine if there is a significant difference in the ability of AHE and CLAHE to depict gray-scale contrast. Observers were presented with computed tomography (CT) images of the chest processed with AHE and CLAHE. Subtle artificial lesions were introduced into some images. The observers were asked to rate their confidence regarding the presence of the lesions; this rating-scale data was analyzed using receiver operating characteristic (ROC) curve techniques. These ROC curves were compared for significant differences in the observers' performances. In this report, no difference was found in the abilities of AHE and CLAHE to depict contrast information.

Measurement of the permeability, perfusion, and histogram characteristics in relapsing-remitting multiple sclerosis using dynamic contrast-enhanced MRI with extended Tofts linear model.

PubMed

Yin, Ping; Xiong, Hua; Liu, Yi; Sah, Shambhu K; Zeng, Chun; Wang, Jingjie; Li, Yongmei; Hong, Nan

2018-01-01

To investigate the application value of using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with extended Tofts linear model for relapsing-remitting multiple sclerosis (RRMS) and its correlation with expanded disability status scale (EDSS) scores and disease duration. Thirty patients with multiple sclerosis (MS) underwent conventional magnetic resonance imaging (MRI) and DCE-MRI with a 3.0 Tesla MR scanner. An extended Tofts linear model was used to quantitatively measure MR imaging biomarkers. The histogram parameters and correlation among imaging biomarkers, EDSS scores, and disease duration were also analyzed. The MR imaging biomarkers volume transfer constant (K trans ), volume of the extravascular extracellular space per unit volume of tissue (Ve), fractional plasma volume (V p ), cerebral blood flow (CBF), and cerebral blood volume (CBV) of contrast-enhancing (CE) lesions were significantly higher (P < 0.05) than those of nonenhancing (NE) lesions and normal-appearing white matter (NAWM) regions. The skewness of Ve value in CE lesions was more close to normal distribution. There was no significant correlation among the biomarkers with the EDSS scores and disease duration (P > 0.05). Our study demonstrates that the DCE-MRI with the extended Tofts linear model can measure the permeability and perfusion characteristic in MS lesions and in NAWM regions. The K trans , Ve, Vp, CBF, and CBV of CE lesions were significantly higher than that of NE lesions. The skewness of Ve value in CE lesions was more close to normal distribution, indicating that the histogram can be helpful to distinguish the pathology of MS lesions.

Analysis of Multi-Scale Radiometric Data Collected during the Cold Land Processes Experiment-1 (CLPX-1)

NASA Technical Reports Server (NTRS)

Tedesco, M.; Kim, E. J.; Gasiewski, A.; Stankov, B.

2005-01-01

Brightness temperature maps at 18.7 and 37 GHz collected at the Fraser and North Park Meso-Scale Areas during the Cold Land Processes Experiment by the NOAA Polarimetric Scanning Radiometer (PSWA) airborne sensor are analyzed. The Fraser site is mostly covered by forest with a typical snowpack depth of 1 m while North Park has no forest cover and is characterized by patches of shallow snow. We examine histograms of the brightness temperatures at 500 m resolution for both the Fraser and North Park areas. The histograms can be modelled by a log-normal distribution in the case of the Fraser MSA and by a bi-modal distribution in the case of the North Park MSA. The histograms of the brightness temperatures at coarser resolutions are also plotted to study the effects of sensor resolution on the shape of the distribution, on the values of the average brightness temperatures and standard deviations. Finally, the values of brightness temperatures obtained by re-sampling (aggregating) the data at 25 km resolution are compared with the values of the brightness temperatures collected by the Advanced Microwave Scanning Radiometer (AMSR-E) and Special Sensor Microwave/Imager (SSMII) satellite radiometers. The results show that in both areas for sensor footprint larger than 5000 m, the brightness temperatures show a flat distribution and the memory of the initial distribution is lost. The values of the brightness temperatures measured by the satellite radiometers are in good agreement with the values obtained averaging the airborne data, even if some discrepancies occur.

DWI-associated entire-tumor histogram analysis for the differentiation of low-grade prostate cancer from intermediate-high-grade prostate cancer.

PubMed

Wu, Chen-Jiang; Wang, Qing; Li, Hai; Wang, Xiao-Ning; Liu, Xi-Sheng; Shi, Hai-Bin; Zhang, Yu-Dong

2015-10-01

To investigate diagnostic efficiency of DWI using entire-tumor histogram analysis in differentiating the low-grade (LG) prostate cancer (PCa) from intermediate-high-grade (HG) PCa in comparison with conventional ROI-based measurement. DW images (b of 0-1400 s/mm(2)) from 126 pathology-confirmed PCa (diameter >0.5 cm) in 110 patients were retrospectively collected and processed by mono-exponential model. The measurement of tumor apparent diffusion coefficients (ADCs) was performed with using histogram-based and ROI-based approach, respectively. The diagnostic ability of ADCs from two methods for differentiating LG-PCa (Gleason score, GS ≤ 6) from HG-PCa (GS > 6) was determined by ROC regression, and compared by McNemar's test. There were 49 LG-tumor and 77 HG-tumor at pathologic findings. Histogram-based ADCs (mean, median, 10th and 90th) and ROI-based ADCs (mean) showed dominant relationships with ordinal GS of Pca (ρ = -0.225 to -0.406, p < 0.05). All above imaging indices reflected significant difference between LG-PCa and HG-PCa (all p values <0.01). Histogram 10th ADCs had dominantly high Az (0.738), Youden index (0.415), and positive likelihood ratio (LR+, 2.45) in stratifying tumor GS against mean, median and 90th ADCs, and ROI-based ADCs. Histogram mean, median, and 10th ADCs showed higher specificity (65.3%-74.1% vs. 44.9%, p < 0.01), but lower sensitivity (57.1%-71.3% vs. 84.4%, p < 0.05) than ROI-based ADCs in differentiating LG-PCa from HG-PCa. DWI-associated histogram analysis had higher specificity, Az, Youden index, and LR+ for differentiation of PCa Gleason grade than ROI-based approach.

Dynamic contrast-enhanced MR imaging of the rectum: Correlations between single-section and whole-tumor histogram analyses.

PubMed

Choi, M H; Oh, S N; Park, G E; Yeo, D-M; Jung, S E

2018-05-10

To evaluate the interobserver and intermethod correlations of histogram metrics of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters acquired by multiple readers using the single-section and whole-tumor volume methods. Four DCE parameters (K trans , K ep , V e , V p ) were evaluated in 45 patients (31 men and 14 women; mean age, 61±11 years [range, 29-83 years]) with locally advanced rectal cancer using pre-chemoradiotherapy (CRT) MRI. Ten histogram metrics were extracted using two methods of lesion selection performed by three radiologists: the whole-tumor volume method for the whole tumor on axial section-by-section images and the single-section method for the entire area of the tumor on one axial image. The interobserver and intermethod correlations were evaluated using the intraclass correlation coefficients (ICCs). The ICCs showed excellent interobserver and intermethod correlations in most of histogram metrics of the DCE parameters. The ICCs among the three readers were > 0.7 (P<0.001) for all histogram metrics, except for the minimum and maximum. The intermethod correlations for most of the histogram metrics were excellent for each radiologist, regardless of the differences in the radiologists' experience. The interobserver and intermethod correlations for most of the histogram metrics of the DCE parameters are excellent in rectal cancer. Therefore, the single-section method may be a potential alternative to the whole-tumor volume method using pre-CRT MRI, despite the fact that the high agreement between the two methods cannot be extrapolated to post-CRT MRI. Copyright © 2018 Société française de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Measuring the apparent diffusion coefficient in primary rectal tumors: is there a benefit in performing histogram analyses?

PubMed

van Heeswijk, Miriam M; Lambregts, Doenja M J; Maas, Monique; Lahaye, Max J; Ayas, Z; Slenter, Jos M G M; Beets, Geerard L; Bakers, Frans C H; Beets-Tan, Regina G H

2017-06-01

The apparent diffusion coefficient (ADC) is a potential prognostic imaging marker in rectal cancer. Typically, mean ADC values are used, derived from precise manual whole-volume tumor delineations by experts. The aim was first to explore whether non-precise circular delineation combined with histogram analysis can be a less cumbersome alternative to acquire similar ADC measurements and second to explore whether histogram analyses provide additional prognostic information. Thirty-seven patients who underwent a primary staging MRI including diffusion-weighted imaging (DWI; b0, 25, 50, 100, 500, 1000; 1.5 T) were included. Volumes-of-interest (VOIs) were drawn on b1000-DWI: (a) precise delineation, manually tracing tumor boundaries (2 expert readers), and (b) non-precise delineation, drawing circular VOIs with a wide margin around the tumor (2 non-experts). Mean ADC and histogram metrics (mean, min, max, median, SD, skewness, kurtosis, 5th-95th percentiles) were derived from the VOIs and delineation time was recorded. Measurements were compared between the two methods and correlated with prognostic outcome parameters. Median delineation time reduced from 47-165 s (precise) to 21-43 s (non-precise). The 45th percentile of the non-precise delineation showed the best correlation with the mean ADC from the precise delineation as the reference standard (ICC 0.71-0.75). None of the mean ADC or histogram parameters showed significant prognostic value; only the total tumor volume (VOI) was significantly larger in patients with positive clinical N stage and mesorectal fascia involvement. When performing non-precise tumor delineation, histogram analysis (in specific 45th ADC percentile) may be used as an alternative to obtain similar ADC values as with precise whole tumor delineation. Histogram analyses are not beneficial to obtain additional prognostic information.

The histogram analysis of diffusion-weighted intravoxel incoherent motion (IVIM) imaging for differentiating the gleason grade of prostate cancer.

PubMed

Zhang, Yu-Dong; Wang, Qing; Wu, Chen-Jiang; Wang, Xiao-Ning; Zhang, Jing; Liu, Hui; Liu, Xi-Sheng; Shi, Hai-Bin

2015-04-01

To evaluate histogram analysis of intravoxel incoherent motion (IVIM) for discriminating the Gleason grade of prostate cancer (PCa). A total of 48 patients pathologically confirmed as having clinically significant PCa (size > 0.5 cm) underwent preoperative DW-MRI (b of 0-900 s/mm(2)). Data was post-processed by monoexponential and IVIM model for quantitation of apparent diffusion coefficients (ADCs), perfusion fraction f, diffusivity D and pseudo-diffusivity D*. Histogram analysis was performed by outlining entire-tumour regions of interest (ROIs) from histological-radiological correlation. The ability of imaging indices to differentiate low-grade (LG, Gleason score (GS) ≤6) from intermediate/high-grade (HG, GS > 6) PCa was analysed by ROC regression. Eleven patients had LG tumours (18 foci) and 37 patients had HG tumours (42 foci) on pathology examination. HG tumours had significantly lower ADCs and D in terms of mean, median, 10th and 75th percentiles, combined with higher histogram kurtosis and skewness for ADCs, D and f, than LG PCa (p < 0.05). Histogram D showed relatively higher correlations (ñ = 0.641-0.668 vs. ADCs: 0.544-0.574) with ordinal GS of PCa; and its mean, median and 10th percentile performed better than ADCs did in distinguishing LG from HG PCa. It is feasible to stratify the pathological grade of PCa by IVIM with histogram metrics. D performed better in distinguishing LG from HG tumour than conventional ADCs. • GS had relatively higher correlation with tumour D than ADCs. • Difference of histogram D among two-grade tumours was statistically significant. • D yielded better individual features in demonstrating tumour grade than ADC. • D* and f failed to determine tumour grade of PCa.

Subtype Differentiation of Small (≤ 4 cm) Solid Renal Mass Using Volumetric Histogram Analysis of DWI at 3-T MRI.

PubMed

Li, Anqin; Xing, Wei; Li, Haojie; Hu, Yao; Hu, Daoyu; Li, Zhen; Kamel, Ihab R

2018-05-29

The purpose of this article is to evaluate the utility of volumetric histogram analysis of apparent diffusion coefficient (ADC) derived from reduced-FOV DWI for small (≤ 4 cm) solid renal mass subtypes at 3-T MRI. This retrospective study included 38 clear cell renal cell carcinomas (RCCs), 16 papillary RCCs, 18 chromophobe RCCs, 13 minimal fat angiomyolipomas (AMLs), and seven oncocytomas evaluated with preoperative MRI. Volumetric ADC maps were generated using all slices of the reduced-FOV DW images to obtain histogram parameters, including mean, median, 10th percentile, 25th percentile, 75th percentile, 90th percentile, and SD ADC values, as well as skewness, kurtosis, and entropy. Comparisons of these parameters were made by one-way ANOVA, t test, and ROC curves analysis. ADC histogram parameters differentiated eight of 10 pairs of renal tumors. Three subtype pairs (clear cell RCC vs papillary RCC, clear cell RCC vs chromophobe RCC, and clear cell RCC vs minimal fat AML) were differentiated by mean ADC. However, five other subtype pairs (clear cell RCC vs oncocytoma, papillary RCC vs minimal fat AML, papillary RCC vs oncocytoma, chromophobe RCC vs minimal fat AML, and chromophobe RCC vs oncocytoma) were differentiated by histogram distribution parameters exclusively (all p < 0.05). Mean ADC, median ADC, 75th and 90th percentile ADC, SD ADC, and entropy of malignant tumors were significantly higher than those of benign tumors (all p < 0.05). Combination of mean ADC with histogram parameters yielded the highest AUC (0.851; sensitivity, 80.0%; specificity, 86.1%). Quantitative volumetric ADC histogram analysis may help differentiate various subtypes of small solid renal tumors, including benign and malignant lesions.

Diffusion-weighted imaging: Apparent diffusion coefficient histogram analysis for detecting pathologic complete response to chemoradiotherapy in locally advanced rectal cancer.

PubMed

Choi, Moon Hyung; Oh, Soon Nam; Rha, Sung Eun; Choi, Joon-Il; Lee, Sung Hak; Jang, Hong Seok; Kim, Jun-Gi; Grimm, Robert; Son, Yohan

2016-07-01

To investigate the usefulness of apparent diffusion coefficient (ADC) values derived from histogram analysis of the whole rectal cancer as a quantitative parameter to evaluate pathologic complete response (pCR) on preoperative magnetic resonance imaging (MRI). We enrolled a total of 86 consecutive patients who had undergone surgery for rectal cancer after neoadjuvant chemoradiotherapy (CRT) at our institution between July 2012 and November 2014. Two radiologists who were blinded to the final pathological results reviewed post-CRT MRI to evaluate tumor stage. Quantitative image analysis was performed using T2 -weighted and diffusion-weighted images independently by two radiologists using dedicated software that performed histogram analysis to assess the distribution of ADC in the whole tumor. After surgery, 16 patients were confirmed to have achieved pCR (18.6%). All parameters from pre- and post-CRT ADC histogram showed good or excellent agreement between two readers. The minimum, 10th, 25th, 50th, and 75th percentile and mean ADC from post-CRT ADC histogram were significantly higher in the pCR group than in the non-pCR group for both readers. The 25th percentile value from ADC histogram in post-CRT MRI had the best diagnostic performance for detecting pCR, with an area under the receiver operating characteristic curve of 0.796. Low percentile values derived from the ADC histogram analysis of rectal cancer on MRI after CRT showed a significant difference between pCR and non-pCR groups, demonstrating the utility of the ADC value as a quantitative and objective marker to evaluate complete pathologic response to preoperative CRT in rectal cancer. J. Magn. Reson. Imaging 2016;44:212-220. © 2015 Wiley Periodicals, Inc.

A Prescription for List-Mode Data Processing Conventions

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

Beddingfield, David H.; Swinhoe, Martyn Thomas; Huszti, Jozsef

There are a variety of algorithmic approaches available to process list-mode pulse streams to produce multiplicity histograms for subsequent analysis. In the development of the INCC v6.0 code to include the processing of this data format, we have noted inconsistencies in the “processed time” between the various approaches. The processed time, tp, is the time interval over which the recorded pulses are analyzed to construct multiplicity histograms. This is the time interval that is used to convert measured counts into count rates. The observed inconsistencies in tp impact the reported count rate information and the determination of the error-values associatedmore » with the derived singles, doubles, and triples counting rates. This issue is particularly important in low count-rate environments. In this report we will present a prescription for the processing of list-mode counting data that produces values that are both correct and consistent with traditional shift-register technologies. It is our objective to define conventions for list mode data processing to ensure that the results are physically valid and numerically aligned with the results from shift-register electronics.« less

Automatic characterization and segmentation of human skin using three-dimensional optical coherence tomography

NASA Astrophysics Data System (ADS)

Hori, Yasuaki; Yasuno, Yoshiaki; Sakai, Shingo; Matsumoto, Masayuki; Sugawara, Tomoko; Madjarova, Violeta; Yamanari, Masahiro; Makita, Shuichi; Yasui, Takeshi; Araki, Tsutomu; Itoh, Masahide; Yatagai, Toyohiko

2006-03-01

A set of fully automated algorithms that is specialized for analyzing a three-dimensional optical coherence tomography (OCT) volume of human skin is reported. The algorithm set first determines the skin surface of the OCT volume, and a depth-oriented algorithm provides the mean epidermal thickness, distribution map of the epidermis, and a segmented volume of the epidermis. Subsequently, an en face shadowgram is produced by an algorithm to visualize the infundibula in the skin with high contrast. The population and occupation ratio of the infundibula are provided by a histogram-based thresholding algorithm and a distance mapping algorithm. En face OCT slices at constant depths from the sample surface are extracted, and the histogram-based thresholding algorithm is again applied to these slices, yielding a three-dimensional segmented volume of the infundibula. The dermal attenuation coefficient is also calculated from the OCT volume in order to evaluate the skin texture. The algorithm set examines swept-source OCT volumes of the skins of several volunteers, and the results show the high stability, portability and reproducibility of the algorithm.

Multifractal diffusion entropy analysis: Optimal bin width of probability histograms

NASA Astrophysics Data System (ADS)

Jizba, Petr; Korbel, Jan

2014-11-01

In the framework of Multifractal Diffusion Entropy Analysis we propose a method for choosing an optimal bin-width in histograms generated from underlying probability distributions of interest. The method presented uses techniques of Rényi’s entropy and the mean squared error analysis to discuss the conditions under which the error in the multifractal spectrum estimation is minimal. We illustrate the utility of our approach by focusing on a scaling behavior of financial time series. In particular, we analyze the S&P500 stock index as sampled at a daily rate in the time period 1950-2013. In order to demonstrate a strength of the method proposed we compare the multifractal δ-spectrum for various bin-widths and show the robustness of the method, especially for large values of q. For such values, other methods in use, e.g., those based on moment estimation, tend to fail for heavy-tailed data or data with long correlations. Connection between the δ-spectrum and Rényi’s q parameter is also discussed and elucidated on a simple example of multiscale time series.

Effects of substrate voltage on noise characteristics and hole lifetime in SOI metal-oxide-semiconductor field-effect transistor photon detector.

PubMed

Putranto, Dedy Septono Catur; Priambodo, Purnomo Sidi; Hartanto, Djoko; Du, Wei; Satoh, Hiroaki; Ono, Atsushi; Inokawa, Hiroshi

2014-09-08

Low-frequency noise and hole lifetime in silicon-on-insulator (SOI) metal-oxide-semiconductor field-effect transistors (MOSFETs) are analyzed, considering their use in photon detection based on single-hole counting. The noise becomes minimum at around the transition point between front- and back-channel operations when the substrate voltage is varied, and increases largely on both negative and positive sides of the substrate voltage showing peculiar Lorentzian (generation-recombination) noise spectra. Hole lifetime is evaluated by the analysis of drain current histogram at different substrate voltages. It is found that the peaks in the histogram corresponding to the larger number of stored holes become higher as the substrate bias becomes larger. This can be attributed to the prolonged lifetime caused by the higher electric field inside the body of SOI MOSFET. It can be concluded that, once the inversion channel is induced for detection of the photo-generated holes, the small absolute substrate bias is favorable for short lifetime and low noise, leading to high-speed operation.

Serial data acquisition for GEM-2D detector

NASA Astrophysics Data System (ADS)

Kolasinski, Piotr; Pozniak, Krzysztof T.; Czarski, Tomasz; Linczuk, Maciej; Byszuk, Adrian; Chernyshova, Maryna; Juszczyk, Bartlomiej; Kasprowicz, Grzegorz; Wojenski, Andrzej; Zabolotny, Wojciech; Zienkiewicz, Pawel; Mazon, Didier; Malard, Philippe; Herrmann, Albrecht; Vezinet, Didier

2014-11-01

This article debates about data fast acquisition and histogramming method for the X-ray GEM detector. The whole process of histogramming is performed by FPGA chips (Spartan-6 series from Xilinx). The results of the histogramming process are stored in an internal FPGA memory and then sent to PC. In PC data is merged and processed by MATLAB. The structure of firmware functionality implemented in the FPGAs is described. Examples of test measurements and results are presented.

A Monte Carlo study of the impact of the choice of rectum volume definition on estimates of equivalent uniform doses and the volume parameter

NASA Astrophysics Data System (ADS)

Kvinnsland, Yngve; Muren, Ludvig Paul; Dahl, Olav

2004-08-01

Calculations of normal tissue complication probability (NTCP) values for the rectum are difficult because it is a hollow, non-rigid, organ. Finding the true cumulative dose distribution for a number of treatment fractions requires a CT scan before each treatment fraction. This is labour intensive, and several surrogate distributions have therefore been suggested, such as dose wall histograms, dose surface histograms and histograms for the solid rectum, with and without margins. In this study, a Monte Carlo method is used to investigate the relationships between the cumulative dose distributions based on all treatment fractions and the above-mentioned histograms that are based on one CT scan only, in terms of equivalent uniform dose. Furthermore, the effect of a specific choice of histogram on estimates of the volume parameter of the probit NTCP model was investigated. It was found that the solid rectum and the rectum wall histograms (without margins) gave equivalent uniform doses with an expected value close to the values calculated from the cumulative dose distributions in the rectum wall. With the number of patients available in this study the standard deviations of the estimates of the volume parameter were large, and it was not possible to decide which volume gave the best estimates of the volume parameter, but there were distinct differences in the mean values of the values obtained.

Detection of Local Tumor Recurrence After Definitive Treatment of Head and Neck Squamous Cell Carcinoma: Histogram Analysis of Dynamic Contrast-Enhanced T1-Weighted Perfusion MRI.

PubMed

Choi, Sang Hyun; Lee, Jeong Hyun; Choi, Young Jun; Park, Ji Eun; Sung, Yu Sub; Kim, Namkug; Baek, Jung Hwan

2017-01-01

This study aimed to explore the added value of histogram analysis of the ratio of initial to final 90-second time-signal intensity AUC (AUCR) for differentiating local tumor recurrence from contrast-enhancing scar on follow-up dynamic contrast-enhanced T1-weighted perfusion MRI of patients treated for head and neck squamous cell carcinoma (HNSCC). AUCR histogram parameters were assessed among tumor recurrence (n = 19) and contrast-enhancing scar (n = 27) at primary sites and compared using the t test. ROC analysis was used to determine the best differentiating parameters. The added value of AUCR histogram parameters was assessed when they were added to inconclusive conventional MRI results. Histogram analysis showed statistically significant differences in the 50th, 75th, and 90th percentiles of the AUCR values between the two groups (p < 0.05). The 90th percentile of the AUCR values (AUCR 90 ) was the best predictor of local tumor recurrence (AUC, 0.77; 95% CI, 0.64-0.91) with an estimated cutoff of 1.02. AUCR 90 increased sensitivity by 11.7% over that of conventional MRI alone when added to inconclusive results. Histogram analysis of AUCR can improve the diagnostic yield for local tumor recurrence during surveillance after treatment for HNSCC.

Value of MR histogram analyses for prediction of microvascular invasion of hepatocellular carcinoma

PubMed Central

Huang, Ya-Qin; Liang, He-Yue; Yang, Zhao-Xia; Ding, Ying; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-01-01

Abstract The objective is to explore the value of preoperative magnetic resonance (MR) histogram analyses in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Fifty-one patients with histologically confirmed HCC who underwent diffusion-weighted and contrast-enhanced MR imaging were included. Histogram analyses were performed and mean, variance, skewness, kurtosis, 1th, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared between HCCs with and without MVI. Receiver operating characteristics (ROC) analyses were generated to compare the diagnostic performance of tumor size, histogram analyses of apparent diffusion coefficient (ADC) maps, and MR enhancement. The mean, 1th, 10th, and 50th percentiles of ADC maps, and the mean, variance. 1th, 10th, 50th, 90th, and 99th percentiles of the portal venous phase (PVP) images were significantly different between the groups with and without MVI (P <0.05), with area under the ROC curves (AUCs) of 0.66 to 0.74 for ADC and 0.76 to 0.88 for PVP. The largest AUC of PVP (1th percentile) showed significantly higher accuracy compared with that of arterial phase (AP) or tumor size (P <0.001). MR histogram analyses—in particular for 1th percentile for PVP images—held promise for prediction of MVI of HCC. PMID:27368028

Effect of respiratory and cardiac gating on the major diffusion-imaging metrics

PubMed Central

Hamaguchi, Hiroyuki; Sugimori, Hiroyuki; Nakanishi, Mitsuhiro; Nakagawa, Shin; Fujiwara, Taro; Yoshida, Hirokazu; Takamori, Sayaka; Shirato, Hiroki

2016-01-01

The effect of respiratory gating on the major diffusion-imaging metrics and that of cardiac gating on mean kurtosis (MK) are not known. For evaluation of whether the major diffusion-imaging metrics—MK, fractional anisotropy (FA), and mean diffusivity (MD) of the brain—varied between gated and non-gated acquisitions, respiratory-gated, cardiac-gated, and non-gated diffusion-imaging of the brain were performed in 10 healthy volunteers. MK, FA, and MD maps were constructed for all acquisitions, and the histograms were constructed. The normalized peak height and location of the histograms were compared among the acquisitions by use of Friedman and post hoc Wilcoxon tests. The effect of the repetition time (TR) on the diffusion-imaging metrics was also tested, and we corrected for its variation among acquisitions, if necessary. The results showed a shift in the peak location of the MK and MD histograms to the right with an increase in TR (p ≤ 0.01). The corrected peak location of the MK histograms, the normalized peak height of the FA histograms, the normalized peak height and the corrected peak location of the MD histograms varied significantly between the gated and non-gated acquisitions (p < 0.05). These results imply an influence of respiration and cardiac pulsation on the major diffusion-imaging metrics. The gating conditions must be kept identical if reproducible results are to be achieved. PMID:27073115

Microdensitometer errors: Their effect on photometric data reduction

NASA Technical Reports Server (NTRS)

Bozyan, E. P.; Opal, C. B.

1984-01-01

The performance of densitometers used for photometric data reduction of high dynamic range electrographic plate material is analyzed. Densitometer repeatability is tested by comparing two scans of one plate. Internal densitometer errors are examined by constructing histograms of digitized densities and finding inoperative bits and differential nonlinearity in the analog to digital converter. Such problems appear common to the four densitometers used in this investigation and introduce systematic algorithm dependent errors in the results. Strategies to improve densitometer performance are suggested.

Histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging can predict histopathological findings including proliferation potential, cellularity, and nucleic areas in head and neck squamous cell carcinoma.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Leifels, Leonard; Höhn, Anne-Kathrin; Richter, Cindy; Winter, Karsten

2018-04-20

Our purpose was to analyze possible associations between histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging DCE MRI and histopathological findings like proliferation index, cell count and nucleic areas in head and neck squamous cell carcinoma (HNSCC). 30 patients (mean age 57.0 years) with primary HNSCC were included in the study. In every case, histogram analysis parameters of K trans , V e , and K ep were estimated using a mathlab based software. Tumor proliferation index, cell count, and nucleic areas were estimated on Ki 67 antigen stained specimens. Spearman's non-parametric rank sum correlation coefficients were calculated between DCE and different histopathological parameters. KI 67 correlated with K trans min ( p = -0.386, P = 0.043) and s K trans skewness ( p = 0.382, P = 0.045), V e min ( p = -0.473, P = 0.011), Ve entropy ( p = 0.424, P = 0.025), and K ep entropy ( p = 0.464, P = 0.013). Cell count correlated with K trans kurtosis ( p = 0.40, P = 0.034), V e entropy ( p = 0.475, P = 0.011). Total nucleic area correlated with V e max ( p = 0.386, P = 0.042) and V e entropy ( p = 0.411, P = 0.030). In G1/2 tumors, only K trans entropy correlated well with total ( P =0.78, P =0.013) and average nucleic areas ( p = 0.655, P = 0.006). In G3 tumors, KI 67 correlated with Ve min ( p = -0.552, P = 0.022) and V e entropy ( p = 0.524, P = 0.031). Ve max correlated with total nucleic area ( p = 0.483, P = 0.049). Kep max correlated with total area ( p = -0.51, P = 0.037), and K ep entropy with KI 67 ( p = 0.567, P = 0.018). We concluded that histogram-based parameters skewness, kurtosis and entropy of K trans , V e , and K ep can be used as markers for proliferation activity, cellularity and nucleic content in HNSCC. Tumor grading influences significantly associations between perfusion and histopathological parameters.

Regionally adaptive histogram equalization of the chest.

PubMed

Sherrier, R H; Johnson, G A

1987-01-01

Advances in the area of digital chest radiography have resulted in the acquisition of high-quality images of the human chest. With these advances, there arises a genuine need for image processing algorithms specific to the chest, in order to fully exploit this digital technology. We have implemented the well-known technique of histogram equalization, noting the problems encountered when it is adapted to chest images. These problems have been successfully solved with our regionally adaptive histogram equalization method. With this technique histograms are calculated locally and then modified according to both the mean pixel value of that region as well as certain characteristics of the cumulative distribution function. This process, which has allowed certain regions of the chest radiograph to be enhanced differentially, may also have broader implications for other image processing tasks.

Infrared face recognition based on LBP histogram and KW feature selection

NASA Astrophysics Data System (ADS)

Xie, Zhihua

2014-07-01

The conventional LBP-based feature as represented by the local binary pattern (LBP) histogram still has room for performance improvements. This paper focuses on the dimension reduction of LBP micro-patterns and proposes an improved infrared face recognition method based on LBP histogram representation. To extract the local robust features in infrared face images, LBP is chosen to get the composition of micro-patterns of sub-blocks. Based on statistical test theory, Kruskal-Wallis (KW) feature selection method is proposed to get the LBP patterns which are suitable for infrared face recognition. The experimental results show combination of LBP and KW features selection improves the performance of infrared face recognition, the proposed method outperforms the traditional methods based on LBP histogram, discrete cosine transform(DCT) or principal component analysis(PCA).

Multispectral histogram normalization contrast enhancement

NASA Technical Reports Server (NTRS)

Soha, J. M.; Schwartz, A. A.

1979-01-01

A multispectral histogram normalization or decorrelation enhancement which achieves effective color composites by removing interband correlation is described. The enhancement procedure employs either linear or nonlinear transformations to equalize principal component variances. An additional rotation to any set of orthogonal coordinates is thus possible, while full histogram utilization is maintained by avoiding the reintroduction of correlation. For the three-dimensional case, the enhancement procedure may be implemented with a lookup table. An application of the enhancement to Landsat multispectral scanning imagery is presented.

Remote logo detection using angle-distance histograms

NASA Astrophysics Data System (ADS)

Youn, Sungwook; Ok, Jiheon; Baek, Sangwook; Woo, Seongyoun; Lee, Chulhee

2016-05-01

Among all the various computer vision applications, automatic logo recognition has drawn great interest from industry as well as various academic institutions. In this paper, we propose an angle-distance map, which we used to develop a robust logo detection algorithm. The proposed angle-distance histogram is invariant against scale and rotation. The proposed method first used shape information and color characteristics to find the candidate regions and then applied the angle-distance histogram. Experiments show that the proposed method detected logos of various sizes and orientations.

Impact of the radiotherapy technique on the correlation between dose-volume histograms of the bladder wall defined on MRI imaging and dose-volume/surface histograms in prostate cancer patients

NASA Astrophysics Data System (ADS)

Maggio, Angelo; Carillo, Viviana; Cozzarini, Cesare; Perna, Lucia; Rancati, Tiziana; Valdagni, Riccardo; Gabriele, Pietro; Fiorino, Claudio

2013-04-01

The aim of this study was to evaluate the correlation between the ‘true’ absolute and relative dose-volume histograms (DVHs) of the bladder wall, dose-wall histogram (DWH) defined on MRI imaging and other surrogates of bladder dosimetry in prostate cancer patients, planned both with 3D-conformal and intensity-modulated radiation therapy (IMRT) techniques. For 17 prostate cancer patients, previously treated with radical intent, CT and MRI scans were acquired and matched. The contours of bladder walls were drawn by using MRI images. External bladder surfaces were then used to generate artificial bladder walls by performing automatic contractions of 5, 7 and 10 mm. For each patient a 3D conformal radiotherapy (3DCRT) and an IMRT treatment plan was generated with a prescription dose of 77.4 Gy (1.8 Gy/fr) and DVH of the whole bladder of the artificial walls (DVH-5/10) and dose-surface histograms (DSHs) were calculated and compared against the DWH in absolute and relative value, for both treatment planning techniques. A specific software (VODCA v. 4.4.0, MSS Inc.) was used for calculating the dose-volume/surface histogram. Correlation was quantified for selected dose-volume/surface parameters by the Spearman correlation coefficient. The agreement between %DWH and DVH5, DVH7 and DVH10 was found to be very good (maximum average deviations below 2%, SD < 5%): DVH5 showed the best agreement. The correlation was slightly better for absolute (R = 0.80-0.94) compared to relative (R = 0.66-0.92) histograms. The DSH was also found to be highly correlated with the DWH, although slightly higher deviations were generally found. The DVH was not a good surrogate of the DWH (R < 0.7 for most of parameters). When comparing the two treatment techniques, more pronounced differences between relative histograms were seen for IMRT with respect to 3DCRT (p < 0.0001).

Quantitative comparison and evaluation of software packages for assessment of abdominal adipose tissue distribution by magnetic resonance imaging.

PubMed

Bonekamp, S; Ghosh, P; Crawford, S; Solga, S F; Horska, A; Brancati, F L; Diehl, A M; Smith, S; Clark, J M

2008-01-01

To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess the reliability of measurement results. Feature evaluation and test-retest reliability of softwares (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision) used in manual, semi-automated or automated segmentation of abdominal adipose tissue. A random sample of 15 obese adults with type 2 diabetes. Axial T1-weighted spin echo images centered at vertebral bodies of L2-L3 were acquired at 1.5 T. Five software packages were evaluated (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision), comparing manual, semi-automated and automated segmentation approaches. Images were segmented into cross-sectional area (CSA), and the areas of visceral (VAT) and subcutaneous adipose tissue (SAT). Ease of learning and use and the design of the graphical user interface (GUI) were rated. Intra-observer accuracy and agreement between the software packages were calculated using intra-class correlation. Intra-class correlation coefficient was used to obtain test-retest reliability. Three of the five evaluated programs offered a semi-automated technique to segment the images based on histogram values or a user-defined threshold. One software package allowed manual delineation only. One fully automated program demonstrated the drawbacks of uncritical automated processing. The semi-automated approaches reduced variability and measurement error, and improved reproducibility. There was no significant difference in the intra-observer agreement in SAT and CSA. The VAT measurements showed significantly lower test-retest reliability. There were some differences between the software packages in qualitative aspects, such as user friendliness. Four out of five packages provided essentially the same results with respect to the inter- and intra-rater reproducibility. Our results using SliceOmatic, Analyze or NIHImage were comparable and could be used interchangeably. Newly developed fully automated approaches should be compared to one of the examined software packages.

Quantitative comparison and evaluation of software packages for assessment of abdominal adipose tissue distribution by magnetic resonance imaging

PubMed Central

Bonekamp, S; Ghosh, P; Crawford, S; Solga, SF; Horska, A; Brancati, FL; Diehl, AM; Smith, S; Clark, JM

2009-01-01

Objective To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess the reliability of measurement results. Design Feature evaluation and test–retest reliability of softwares (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision) used in manual, semi-automated or automated segmentation of abdominal adipose tissue. Subjects A random sample of 15 obese adults with type 2 diabetes. Measurements Axial T1-weighted spin echo images centered at vertebral bodies of L2–L3 were acquired at 1.5 T. Five software packages were evaluated (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision), comparing manual, semi-automated and automated segmentation approaches. Images were segmented into cross-sectional area (CSA), and the areas of visceral (VAT) and subcutaneous adipose tissue (SAT). Ease of learning and use and the design of the graphical user interface (GUI) were rated. Intra-observer accuracy and agreement between the software packages were calculated using intra-class correlation. Intra-class correlation coefficient was used to obtain test–retest reliability. Results Three of the five evaluated programs offered a semi-automated technique to segment the images based on histogram values or a user-defined threshold. One software package allowed manual delineation only. One fully automated program demonstrated the drawbacks of uncritical automated processing. The semi-automated approaches reduced variability and measurement error, and improved reproducibility. There was no significant difference in the intra-observer agreement in SAT and CSA. The VAT measurements showed significantly lower test–retest reliability. There were some differences between the software packages in qualitative aspects, such as user friendliness. Conclusion Four out of five packages provided essentially the same results with respect to the inter- and intra-rater reproducibility. Our results using SliceOmatic, Analyze or NIHImage were comparable and could be used interchangeably. Newly developed fully automated approaches should be compared to one of the examined software packages. PMID:17700582

RATIO_TOOL - SOFTWARE FOR COMPUTING IMAGE RATIOS

NASA Technical Reports Server (NTRS)

Yates, G. L.

1994-01-01

Geological studies analyze spectral data in order to gain information on surface materials. RATIO_TOOL is an interactive program for viewing and analyzing large multispectral image data sets that have been created by an imaging spectrometer. While the standard approach to classification of multispectral data is to match the spectrum for each input pixel against a library of known mineral spectra, RATIO_TOOL uses ratios of spectral bands in order to spot significant areas of interest within a multispectral image. Each image band can be viewed iteratively, or a selected image band of the data set can be requested and displayed. When the image ratios are computed, the result is displayed as a gray scale image. At this point a histogram option helps in viewing the distribution of values. A thresholding option can then be used to segment the ratio image result into two to four classes. The segmented image is then color coded to indicate threshold classes and displayed alongside the gray scale image. RATIO_TOOL is written in C language for Sun series computers running SunOS 4.0 and later. It requires the XView toolkit and the OpenWindows window manager (version 2.0 or 3.0). The XView toolkit is distributed with Open Windows. A color monitor is also required. The standard distribution medium for RATIO_TOOL is a .25 inch streaming magnetic tape cartridge in UNIX tar format. An electronic copy of the documentation is included on the program media. RATIO_TOOL was developed in 1992 and is a copyrighted work with all copyright vested in NASA. Sun, SunOS, and OpenWindows are trademarks of Sun Microsystems, Inc. UNIX is a registered trademark of AT&T Bell Laboratories.

Poster — Thur Eve — 69: Computational Study of DVH-guided Cancer Treatment Planning Optimization Methods

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

Ghomi, Pooyan Shirvani; Zinchenko, Yuriy

2014-08-15

Purpose: To compare methods to incorporate the Dose Volume Histogram (DVH) curves into the treatment planning optimization. Method: The performance of three methods, namely, the conventional Mixed Integer Programming (MIP) model, a convex moment-based constrained optimization approach, and an unconstrained convex moment-based penalty approach, is compared using anonymized data of a prostate cancer patient. Three plans we generated using the corresponding optimization models. Four Organs at Risk (OARs) and one Tumor were involved in the treatment planning. The OARs and Tumor were discretized into total of 50,221 voxels. The number of beamlets was 943. We used commercially available optimization softwaremore » Gurobi and Matlab to solve the models. Plan comparison was done by recording the model runtime followed by visual inspection of the resulting dose volume histograms. Conclusion: We demonstrate the effectiveness of the moment-based approaches to replicate the set of prescribed DVH curves. The unconstrained convex moment-based penalty approach is concluded to have the greatest potential to reduce the computational effort and holds a promise of substantial computational speed up.« less

Histograms and Raisin Bread

ERIC Educational Resources Information Center

Leyden, Michael B.

1975-01-01

Describes various elementary school activities using a loaf of raisin bread to promote inquiry skills. Activities include estimating the number of raisins in the loaf by constructing histograms of the number of raisins in a slice. (MLH)

Infrared small target enhancement: grey level mapping based on improved sigmoid transformation and saliency histogram

NASA Astrophysics Data System (ADS)

Wan, Minjie; Gu, Guohua; Qian, Weixian; Ren, Kan; Chen, Qian

2018-06-01

Infrared (IR) small target enhancement plays a significant role in modern infrared search and track (IRST) systems and is the basic technique of target detection and tracking. In this paper, a coarse-to-fine grey level mapping method using improved sigmoid transformation and saliency histogram is designed to enhance IR small targets under different backgrounds. For the stage of rough enhancement, the intensity histogram is modified via an improved sigmoid function so as to narrow the regular intensity range of background as much as possible. For the part of further enhancement, a linear transformation is accomplished based on a saliency histogram constructed by averaging the cumulative saliency values provided by a saliency map. Compared with other typical methods, the presented method can achieve both better visual performances and quantitative evaluations.

A domain-knowledge-inspired mathematical framework for the description and classification of H&E stained histopathology images.

PubMed

Massar, Melody L; Bhagavatula, Ramamurthy; Ozolek, John A; Castro, Carlos A; Fickus, Matthew; Kovačević, Jelena

2011-10-19

We present the current state of our work on a mathematical framework for identification and delineation of histopathology images-local histograms and occlusion models. Local histograms are histograms computed over defined spatial neighborhoods whose purpose is to characterize an image locally. This unit of description is augmented by our occlusion models that describe a methodology for image formation. In the context of this image formation model, the power of local histograms with respect to appropriate families of images will be shown through various proved statements about expected performance. We conclude by presenting a preliminary study to demonstrate the power of the framework in the context of histopathology image classification tasks that, while differing greatly in application, both originate from what is considered an appropriate class of images for this framework.

[Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

PubMed

Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

2013-12-01

To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors.

PubMed

Cho, Gene Young; Moy, Linda; Kim, Sungheon G; Baete, Steven H; Moccaldi, Melanie; Babb, James S; Sodickson, Daniel K; Sigmund, Eric E

2016-08-01

To examine heterogeneous breast cancer through intravoxel incoherent motion (IVIM) histogram analysis. This HIPAA-compliant, IRB-approved retrospective study included 62 patients (age 48.44 ± 11.14 years, 50 malignant lesions and 12 benign) who underwent contrast-enhanced 3 T breast MRI and diffusion-weighted imaging. Apparent diffusion coefficient (ADC) and IVIM biomarkers of tissue diffusivity (Dt), perfusion fraction (fp), and pseudo-diffusivity (Dp) were calculated using voxel-based analysis for the whole lesion volume. Histogram analysis was performed to quantify tumour heterogeneity. Comparisons were made using Mann-Whitney tests between benign/malignant status, histological subtype, and molecular prognostic factor status while Spearman's rank correlation was used to characterize the association between imaging biomarkers and prognostic factor expression. The average values of the ADC and IVIM biomarkers, Dt and fp, showed significant differences between benign and malignant lesions. Additional significant differences were found in the histogram parameters among tumour subtypes and molecular prognostic factor status. IVIM histogram metrics, particularly fp and Dp, showed significant correlation with hormonal factor expression. Advanced diffusion imaging biomarkers show relationships with molecular prognostic factors and breast cancer malignancy. This analysis reveals novel diagnostic metrics that may explain some of the observed variability in treatment response among breast cancer patients. • Novel IVIM biomarkers characterize heterogeneous breast cancer. • Histogram analysis enables quantification of tumour heterogeneity. • IVIM biomarkers show relationships with breast cancer malignancy and molecular prognostic factors.

Whole-tumor histogram analysis of the cerebral blood volume map: tumor volume defined by 11C-methionine positron emission tomography image improves the diagnostic accuracy of cerebral glioma grading.

PubMed

Wu, Rongli; Watanabe, Yoshiyuki; Arisawa, Atsuko; Takahashi, Hiroto; Tanaka, Hisashi; Fujimoto, Yasunori; Watabe, Tadashi; Isohashi, Kayako; Hatazawa, Jun; Tomiyama, Noriyuki

2017-10-01

This study aimed to compare the tumor volume definition using conventional magnetic resonance (MR) and 11C-methionine positron emission tomography (MET/PET) images in the differentiation of the pre-operative glioma grade by using whole-tumor histogram analysis of normalized cerebral blood volume (nCBV) maps. Thirty-four patients with histopathologically proven primary brain low-grade gliomas (n = 15) and high-grade gliomas (n = 19) underwent pre-operative or pre-biopsy MET/PET, fluid-attenuated inversion recovery, dynamic susceptibility contrast perfusion-weighted magnetic resonance imaging, and contrast-enhanced T1-weighted at 3.0 T. The histogram distribution derived from the nCBV maps was obtained by co-registering the whole tumor volume delineated on conventional MR or MET/PET images, and eight histogram parameters were assessed. The mean nCBV value had the highest AUC value (0.906) based on MET/PET images. Diagnostic accuracy significantly improved when the tumor volume was measured from MET/PET images compared with conventional MR images for the parameters of mean, 50th, and 75th percentile nCBV value (p = 0.0246, 0.0223, and 0.0150, respectively). Whole-tumor histogram analysis of CBV map provides more valuable histogram parameters and increases diagnostic accuracy in the differentiation of pre-operative cerebral gliomas when the tumor volume is derived from MET/PET images.

Effect of respiratory and cardiac gating on the major diffusion-imaging metrics.

PubMed

Hamaguchi, Hiroyuki; Tha, Khin Khin; Sugimori, Hiroyuki; Nakanishi, Mitsuhiro; Nakagawa, Shin; Fujiwara, Taro; Yoshida, Hirokazu; Takamori, Sayaka; Shirato, Hiroki

2016-08-01

The effect of respiratory gating on the major diffusion-imaging metrics and that of cardiac gating on mean kurtosis (MK) are not known. For evaluation of whether the major diffusion-imaging metrics-MK, fractional anisotropy (FA), and mean diffusivity (MD) of the brain-varied between gated and non-gated acquisitions, respiratory-gated, cardiac-gated, and non-gated diffusion-imaging of the brain were performed in 10 healthy volunteers. MK, FA, and MD maps were constructed for all acquisitions, and the histograms were constructed. The normalized peak height and location of the histograms were compared among the acquisitions by use of Friedman and post hoc Wilcoxon tests. The effect of the repetition time (TR) on the diffusion-imaging metrics was also tested, and we corrected for its variation among acquisitions, if necessary. The results showed a shift in the peak location of the MK and MD histograms to the right with an increase in TR (p ≤ 0.01). The corrected peak location of the MK histograms, the normalized peak height of the FA histograms, the normalized peak height and the corrected peak location of the MD histograms varied significantly between the gated and non-gated acquisitions (p < 0.05). These results imply an influence of respiration and cardiac pulsation on the major diffusion-imaging metrics. The gating conditions must be kept identical if reproducible results are to be achieved. © The Author(s) 2016.

A comparative study on preprocessing techniques in diabetic retinopathy retinal images: illumination correction and contrast enhancement.

PubMed

Rasta, Seyed Hossein; Partovi, Mahsa Eisazadeh; Seyedarabi, Hadi; Javadzadeh, Alireza

2015-01-01

To investigate the effect of preprocessing techniques including contrast enhancement and illumination correction on retinal image quality, a comparative study was carried out. We studied and implemented a few illumination correction and contrast enhancement techniques on color retinal images to find out the best technique for optimum image enhancement. To compare and choose the best illumination correction technique we analyzed the corrected red and green components of color retinal images statistically and visually. The two contrast enhancement techniques were analyzed using a vessel segmentation algorithm by calculating the sensitivity and specificity. The statistical evaluation of the illumination correction techniques were carried out by calculating the coefficients of variation. The dividing method using the median filter to estimate background illumination showed the lowest Coefficients of variations in the red component. The quotient and homomorphic filtering methods after the dividing method presented good results based on their low Coefficients of variations. The contrast limited adaptive histogram equalization increased the sensitivity of the vessel segmentation algorithm up to 5% in the same amount of accuracy. The contrast limited adaptive histogram equalization technique has a higher sensitivity than the polynomial transformation operator as a contrast enhancement technique for vessel segmentation. Three techniques including the dividing method using the median filter to estimate background, quotient based and homomorphic filtering were found as the effective illumination correction techniques based on a statistical evaluation. Applying the local contrast enhancement technique, such as CLAHE, for fundus images presented good potentials in enhancing the vasculature segmentation.

Pattern-histogram-based temporal change detection using personal chest radiographs

NASA Astrophysics Data System (ADS)

Ugurlu, Yucel; Obi, Takashi; Hasegawa, Akira; Yamaguchi, Masahiro; Ohyama, Nagaaki

1999-05-01

An accurate and reliable detection of temporal changes from a pair of images has considerable interest in the medical science. Traditional registration and subtraction techniques can be applied to extract temporal differences when,the object is rigid or corresponding points are obvious. However, in radiological imaging, loss of the depth information, the elasticity of object, the absence of clearly defined landmarks and three-dimensional positioning differences constraint the performance of conventional registration techniques. In this paper, we propose a new method in order to detect interval changes accurately without using an image registration technique. The method is based on construction of so-called pattern histogram and comparison procedure. The pattern histogram is a graphic representation of the frequency counts of all allowable patterns in the multi-dimensional pattern vector space. K-means algorithm is employed to partition pattern vector space successively. Any differences in the pattern histograms imply that different patterns are involved in the scenes. In our experiment, a pair of chest radiographs of pneumoconiosis is employed and the changing histogram bins are visualized on both of the images. We found that the method can be used as an alternative way of temporal change detection, particularly when the precise image registration is not available.

A Concise Guide to Feature Histograms with Applications to LIDAR-Based Spacecraft Relative Navigation

NASA Astrophysics Data System (ADS)

Rhodes, Andrew P.; Christian, John A.; Evans, Thomas

2017-12-01

With the availability and popularity of 3D sensors, it is advantageous to re-examine the use of point cloud descriptors for the purpose of pose estimation and spacecraft relative navigation. One popular descriptor is the oriented unique repeatable clustered viewpoint feature histogram (OUR-CVFH), which is most often utilized in personal and industrial robotics to simultaneously recognize and navigate relative to an object. Recent research into using the OUR-CVFH descriptor for spacecraft navigation has produced favorable results. Since OUR-CVFH is the most recent innovation in a large family of feature histogram point cloud descriptors, discussions of parameter settings and insights into its functionality are spread among various publications and online resources. This paper organizes the history of feature histogram point cloud descriptors for a straightforward explanation of their evolution. This article compiles all the requisite information needed to implement OUR-CVFH into one location, as well as providing useful suggestions on how to tune the generation parameters. This work is beneficial for anyone interested in using this histogram descriptor for object recognition or navigation - may it be personal robotics or spacecraft navigation.

Improved LSB matching steganography with histogram characters reserved

NASA Astrophysics Data System (ADS)

Chen, Zhihong; Liu, Wenyao

2008-03-01

This letter bases on the researches of LSB (least significant bit, i.e. the last bit of a binary pixel value) matching steganographic method and the steganalytic method which aims at histograms of cover images, and proposes a modification to LSB matching. In the LSB matching, if the LSB of the next cover pixel matches the next bit of secret data, do nothing; otherwise, choose to add or subtract one from the cover pixel value at random. In our improved method, a steganographic information table is defined and records the changes which embedded secrete bits introduce in. Through the table, the next LSB which has the same pixel value will be judged to add or subtract one dynamically in order to ensure the histogram's change of cover image is minimized. Therefore, the modified method allows embedding the same payload as the LSB matching but with improved steganographic security and less vulnerability to attacks compared with LSB matching. The experimental results of the new method show that the histograms maintain their attributes, such as peak values and alternative trends, in an acceptable degree and have better performance than LSB matching in the respects of histogram distortion and resistance against existing steganalysis.

Histograms and Frequency Density.

ERIC Educational Resources Information Center

Micromath, 2003

2003-01-01

Introduces exercises on histograms and frequency density. Guides pupils to Discovering Important Statistical Concepts Using Spreadsheets (DISCUSS), created at the University of Coventry. Includes curriculum points, teaching tips, activities, and internet address (http://www.coventry.ac.uk/discuss/). (KHR)

Temperature factors effect on occurrence of stress corrosion cracking of main gas pipeline

NASA Astrophysics Data System (ADS)

Nazarova, M. N.; Akhmetov, R. R.; Krainov, S. A.

2017-10-01

The purpose of the article is to analyze and compare the data in order to contribute to the formation of an objective opinion on the issue of the growth of stress corrosion defects of the main gas pipeline. According to available data, a histogram of the dependence of defects due to stress corrosion on the distance from the compressor station was constructed, and graphs of the dependence of the accident density due to stress corrosion in the winter and summer were also plotted. Data on activation energy were collected and analyzed in which occurrence of stress corrosion is most likely constructed, a plot of activation energy versus temperature is plotted, and the process of occurrence of stress corrosion by the example of two different grades of steels under the action of different temperatures was analyzed.

The DataCube Server. Animate Agent Project Working Note 2, Version 1.0

DTIC Science & Technology

1993-11-01

before this can be called a histogram of all the needed levels must be made and their one band images must be made. Note if a levels backprojection...will not be used then the level does not need to be histogrammed. Any points outside the active region in a levels backprojection will be undefined...this can be called a histogram of all the needed levels must be made and their one band images must be made. Note if a levels backprojection will not

IN VITRO QUANTIFICATION OF THE SIZE DISTRIBUTION OF INTRASACCULAR VOIDS LEFT AFTER ENDOVASCULAR COILING OF CEREBRAL ANEURYSMS.

PubMed

Sadasivan, Chander; Brownstein, Jeremy; Patel, Bhumika; Dholakia, Ronak; Santore, Joseph; Al-Mufti, Fawaz; Puig, Enrique; Rakian, Audrey; Fernandez-Prada, Kenneth D; Elhammady, Mohamed S; Farhat, Hamad; Fiorella, David J; Woo, Henry H; Aziz-Sultan, Mohammad A; Lieber, Baruch B

2013-03-01

Endovascular coiling of cerebral aneurysms remains limited by coil compaction and associated recanalization. Recent coil designs which effect higher packing densities may be far from optimal because hemodynamic forces causing compaction are not well understood since detailed data regarding the location and distribution of coil masses are unavailable. We present an in vitro methodology to characterize coil masses deployed within aneurysms by quantifying intra-aneurysmal void spaces. Eight identical aneurysms were packed with coils by both balloon- and stent-assist techniques. The samples were embedded, sequentially sectioned and imaged. Empty spaces between the coils were numerically filled with circles (2D) in the planar images and with spheres (3D) in the three-dimensional composite images. The 2D and 3D void size histograms were analyzed for local variations and by fitting theoretical probability distribution functions. Balloon-assist packing densities (31±2%) were lower ( p =0.04) than the stent-assist group (40±7%). The maximum and average 2D and 3D void sizes were higher ( p =0.03 to 0.05) in the balloon-assist group as compared to the stent-assist group. None of the void size histograms were normally distributed; theoretical probability distribution fits suggest that the histograms are most probably exponentially distributed with decay constants of 6-10 mm. Significant ( p <=0.001 to p =0.03) spatial trends were noted with the void sizes but correlation coefficients were generally low (absolute r <=0.35). The methodology we present can provide valuable input data for numerical calculations of hemodynamic forces impinging on intra-aneurysmal coil masses and be used to compare and optimize coil configurations as well as coiling techniques.

Sonoelastography of the plantar fascia.

PubMed

Wu, Chueh-Hung; Chang, Ke-Vin; Mio, Sun; Chen, Wen-Shiang; Wang, Tyng-Guey

2011-05-01

To compare the stiffness of the plantar fascia by using sonoelastography in healthy subjects of different ages, as well as patients with plantar fasciitis. The study protocol was approved by the Research Ethics Committee of the hospital, and all of the subjects gave their informed consent. Bilateral feet of 40 healthy subjects and 13 subjects with plantar fasciitis (fasciitis group) were examined by using color-coded sonoelastography. Healthy subjects were divided into younger (18-50 years) and older (> 50 years) groups. The color scheme was red (hard), green (medium stiffness), and blue (soft). The color histogram was subsequently analyzed. Each pixel of the image was separated into red, green, and blue components (color intensity range, 0-255). The color histogram then computed the mean intensity of each color component of the pixels within a standardized area. Mixed model for repeated measurements was used for comparison of the plantar fascia thickness and the intensity of the color components on sonoelastogram. Quantitative analysis of the color histogram revealed a significantly greater intensity of blue in older healthy subjects than in younger (94.5 ± 5.6 [± standard deviation] vs 90.0 ± 4.6, P = .002) subjects. The intensity of red and green was the same between younger and older healthy subjects (P = .68 and 0.12). The intensity of red was significantly greater in older healthy subjects than in the fasciitis group (147.8 ± 10.3 vs 133.7 ± 13.4, P < .001). The intensity of green and blue was the same between older healthy subjects and those in the fasciitis group (P = .33 and .71). Sonoelastography revealed that the plantar fascia softens with age and in subjects with plantar fasciitis. RSNA, 2011

APT: Aperture Photometry Tool

NASA Astrophysics Data System (ADS)

Laher, Russ

2012-08-01

Aperture Photometry Tool (APT) is software for astronomers and students interested in manually exploring the photometric qualities of astronomical images. It has a graphical user interface (GUI) which allows the image data associated with aperture photometry calculations for point and extended sources to be visualized and, therefore, more effectively analyzed. Mouse-clicking on a source in the displayed image draws a circular or elliptical aperture and sky annulus around the source and computes the source intensity and its uncertainty, along with several commonly used measures of the local sky background and its variability. The results are displayed and can be optionally saved to an aperture-photometry-table file and plotted on graphs in various ways using functions available in the software. APT is geared toward processing sources in a small number of images and is not suitable for bulk processing a large number of images, unlike other aperture photometry packages (e.g., SExtractor). However, APT does have a convenient source-list tool that enables calculations for a large number of detections in a given image. The source-list tool can be run either in automatic mode to generate an aperture photometry table quickly or in manual mode to permit inspection and adjustment of the calculation for each individual detection. APT displays a variety of useful graphs, including image histogram, and aperture slices, source scatter plot, sky scatter plot, sky histogram, radial profile, curve of growth, and aperture-photometry-table scatter plots and histograms. APT has functions for customizing calculations, including outlier rejection, pixel “picking” and “zapping,” and a selection of source and sky models. The radial-profile-interpolation source model, accessed via the radial-profile-plot panel, allows recovery of source intensity from pixels with missing data and can be especially beneficial in crowded fields.

rFRET: A comprehensive, Matlab-based program for analyzing intensity-based ratiometric microscopic FRET experiments.

PubMed

Nagy, Peter; Szabó, Ágnes; Váradi, Tímea; Kovács, Tamás; Batta, Gyula; Szöllősi, János

2016-04-01

Fluorescence or Förster resonance energy transfer (FRET) remains one of the most widely used methods for assessing protein clustering and conformation. Although it is a method with solid physical foundations, many applications of FRET fall short of providing quantitative results due to inappropriate calibration and controls. This shortcoming is especially valid for microscopy where currently available tools have limited or no capability at all to display parameter distributions or to perform gating. Since users of multiparameter flow cytometry usually apply these tools, the absence of these features in applications developed for microscopic FRET analysis is a significant limitation. Therefore, we developed a graphical user interface-controlled Matlab application for the evaluation of ratiometric, intensity-based microscopic FRET measurements. The program can calculate all the necessary overspill and spectroscopic correction factors and the FRET efficiency and it displays the results on histograms and dot plots. Gating on plots and mask images can be used to limit the calculation to certain parts of the image. It is an important feature of the program that the calculated parameters can be determined by regression methods, maximum likelihood estimation (MLE) and from summed intensities in addition to pixel-by-pixel evaluation. The confidence interval of calculated parameters can be estimated using parameter simulations if the approximate average number of detected photons is known. The program is not only user-friendly, but it provides rich output, it gives the user freedom to choose from different calculation modes and it gives insight into the reliability and distribution of the calculated parameters. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

Computer program for prediction of fuel consumption statistical data for an upper stage three-axes stabilized on-off control system

NASA Technical Reports Server (NTRS)

1982-01-01

A FORTRAN coded computer program and method to predict the reaction control fuel consumption statistics for a three axis stabilized rocket vehicle upper stage is described. A Monte Carlo approach is used which is more efficient by using closed form estimates of impulses. The effects of rocket motor thrust misalignment, static unbalance, aerodynamic disturbances, and deviations in trajectory, mass properties and control system characteristics are included. This routine can be applied to many types of on-off reaction controlled vehicles. The pseudorandom number generation and statistical analyses subroutines including the output histograms can be used for other Monte Carlo analyses problems.

Diffusion Profiling via a Histogram Approach Distinguishes Low-grade from High-grade Meningiomas, Can Reflect the Respective Proliferative Potential and Progesterone Receptor Status.

PubMed

Gihr, Georg Alexander; Horvath-Rizea, Diana; Garnov, Nikita; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Henkes, Hans; Meyer, Hans Jonas; Hoffmann, Karl-Titus; Surov, Alexey; Schob, Stefan

2018-02-01

Presurgical grading, estimation of growth kinetics, and other prognostic factors are becoming increasingly important for selecting the best therapeutic approach for meningioma patients. Diffusion-weighted imaging (DWI) provides microstructural information and reflects tumor biology. A novel DWI approach, histogram profiling of apparent diffusion coefficient (ADC) volumes, provides more distinct information than conventional DWI. Therefore, our study investigated whether ADC histogram profiling distinguishes low-grade from high-grade lesions and reflects Ki-67 expression and progesterone receptor status. Pretreatment ADC volumes of 37 meningioma patients (28 low-grade, 9 high-grade) were used for histogram profiling. WHO grade, Ki-67 expression, and progesterone receptor status were evaluated. Comparative and correlative statistics investigating the association between histogram profiling and neuropathology were performed. The entire ADC profile (p10, p25, p75, p90, mean, median) was significantly lower in high-grade versus low-grade meningiomas. The lower percentiles, mean, and modus showed significant correlations with Ki-67 expression. Skewness and entropy of the ADC volumes were significantly associated with progesterone receptor status and Ki-67 expression. ROC analysis revealed entropy to be the most accurate parameter distinguishing low-grade from high-grade meningiomas. ADC histogram profiling provides a distinct set of parameters, which help differentiate low-grade versus high-grade meningiomas. Also, histogram metrics correlate significantly with histological surrogates of the respective proliferative potential. More specifically, entropy revealed to be the most promising imaging biomarker for presurgical grading. Both, entropy and skewness were significantly associated with progesterone receptor status and Ki-67 expression and therefore should be investigated further as predictors for prognostically relevant tumor biological features. Since absolute ADC values vary between MRI scanners of different vendors and field strengths, their use is more limited in the presurgical setting.

ADC histogram analysis for adrenal tumor histogram analysis of apparent diffusion coefficient in differentiating adrenal adenoma from pheochromocytoma.

PubMed

Umanodan, Tomokazu; Fukukura, Yoshihiko; Kumagae, Yuichi; Shindo, Toshikazu; Nakajo, Masatoyo; Takumi, Koji; Nakajo, Masanori; Hakamada, Hiroto; Umanodan, Aya; Yoshiura, Takashi

2017-04-01

To determine the diagnostic performance of apparent diffusion coefficient (ADC) histogram analysis in diffusion-weighted (DW) magnetic resonance imaging (MRI) for differentiating adrenal adenoma from pheochromocytoma. We retrospectively evaluated 52 adrenal tumors (39 adenomas and 13 pheochromocytomas) in 47 patients (21 men, 26 women; mean age, 59.3 years; range, 16-86 years) who underwent DW 3.0T MRI. Histogram parameters of ADC (b-values of 0 and 200 [ADC 200 ], 0 and 400 [ADC 400 ], and 0 and 800 s/mm 2 [ADC 800 ])-mean, variance, coefficient of variation (CV), kurtosis, skewness, and entropy-were compared between adrenal adenomas and pheochromocytomas, using the Mann-Whitney U-test. Receiver operating characteristic (ROC) curves for the histogram parameters were generated to differentiate adrenal adenomas from pheochromocytomas. Sensitivity and specificity were calculated by using a threshold criterion that would maximize the average of sensitivity and specificity. Variance and CV of ADC 800 were significantly higher in pheochromocytomas than in adrenal adenomas (P < 0.001 and P = 0.001, respectively). With all b-value combinations, the entropy of ADC was significantly higher in pheochromocytomas than in adrenal adenomas (all P ≤ 0.001), and showed the highest area under the ROC curve among the ADC histogram parameters for diagnosing adrenal adenomas (ADC 200 , 0.82; ADC 400 , 0.87; and ADC 800 , 0.92), with sensitivity of 84.6% and specificity of 84.6% (cutoff, ≤2.82) with ADC 200 ; sensitivity of 89.7% and specificity of 84.6% (cutoff, ≤2.77) with ADC 400 ; and sensitivity of 94.9% and specificity of 92.3% (cutoff, ≤2.67) with ADC 800 . ADC histogram analysis of DW MRI can help differentiate adrenal adenoma from pheochromocytoma. 3 J. Magn. Reson. Imaging 2017;45:1195-1203. © 2016 International Society for Magnetic Resonance in Medicine.

Robust Audio Watermarking by Using Low-Frequency Histogram

NASA Astrophysics Data System (ADS)

Xiang, Shijun

In continuation to earlier work where the problem of time-scale modification (TSM) has been studied [1] by modifying the shape of audio time domain histogram, here we consider the additional ingredient of resisting additive noise-like operations, such as Gaussian noise, lossy compression and low-pass filtering. In other words, we study the problem of the watermark against both TSM and additive noises. To this end, in this paper we extract the histogram from a Gaussian-filtered low-frequency component for audio watermarking. The watermark is inserted by shaping the histogram in a way that the use of two consecutive bins as a group is exploited for hiding a bit by reassigning their population. The watermarked signals are perceptibly similar to the original one. Comparing with the previous time-domain watermarking scheme [1], the proposed watermarking method is more robust against additive noise, MP3 compression, low-pass filtering, etc.

LSAH: a fast and efficient local surface feature for point cloud registration

NASA Astrophysics Data System (ADS)

Lu, Rongrong; Zhu, Feng; Wu, Qingxiao; Kong, Yanzi

2018-04-01

Point cloud registration is a fundamental task in high level three dimensional applications. Noise, uneven point density and varying point cloud resolutions are the three main challenges for point cloud registration. In this paper, we design a robust and compact local surface descriptor called Local Surface Angles Histogram (LSAH) and propose an effectively coarse to fine algorithm for point cloud registration. The LSAH descriptor is formed by concatenating five normalized sub-histograms into one histogram. The five sub-histograms are created by accumulating a different type of angle from a local surface patch respectively. The experimental results show that our LSAH is more robust to uneven point density and point cloud resolutions than four state-of-the-art local descriptors in terms of feature matching. Moreover, we tested our LSAH based coarse to fine algorithm for point cloud registration. The experimental results demonstrate that our algorithm is robust and efficient as well.

Advanced concentration analysis of atom probe tomography data: Local proximity histograms and pseudo-2D concentration maps.

PubMed

Felfer, Peter; Cairney, Julie

2018-06-01

Analysing the distribution of selected chemical elements with respect to interfaces is one of the most common tasks in data mining in atom probe tomography. This can be represented by 1D concentration profiles, 2D concentration maps or proximity histograms, which represent concentration, density etc. of selected species as a function of the distance from a reference surface/interface. These are some of the most useful tools for the analysis of solute distributions in atom probe data. In this paper, we present extensions to the proximity histogram in the form of 'local' proximity histograms, calculated for selected parts of a surface, and pseudo-2D concentration maps, which are 2D concentration maps calculated on non-flat surfaces. This way, local concentration changes at interfaces or and other structures can be assessed more effectively. Copyright © 2018 Elsevier B.V. All rights reserved.

Evaluation of digital radiography practice using exposure index tracking

PubMed Central

Zhou, Yifang; Allahverdian, Janet; Nute, Jessica L.; Lee, Christina

2016-01-01

Some digital radiography (DR) detectors and software allow for remote download of exam statistics, including image reject status, body part, projection, and exposure index (EI). The ability to have automated data collection from multiple DR units is conducive to a quality control (QC) program monitoring institutional radiographic exposures. We have implemented such a QC program with the goal to identify outliers in machine radiation output and opportunities for improvement in radiation dose levels. We studied the QC records of four digital detectors in greater detail on a monthly basis for one year. Although individual patient entrance skin exposure varied, the radiation dose levels to the detectors were made to be consistent via phototimer recalibration. The exposure data stored on each digital detector were periodically downloaded in a spreadsheet format for analysis. EI median and standard deviation were calculated for each protocol (by body part) and EI histograms were created for torso protocols. When histograms of EI values for different units were compared, we observed differences up to 400 in average EI (representing 60% difference in radiation levels to the detector) between units nominally calibrated to the same EI. We identified distinct components of the EI distributions, which in some cases, had mean EI values 300 apart. Peaks were observed at the current calibrated EI, a previously calibrated EI, and an EI representing computed radiography (CR) techniques. Our findings in this ongoing project have allowed us to make useful interventions, from emphasizing the use of phototimers instead of institutional memory of manual techniques to improvements in our phototimer calibration. We believe that this QC program can be implemented at other sites and can reveal problems with radiation levels in the aggregate that are difficult to identify on a case‐by‐case basis. PACS number(s): 87.59.bf PMID:27929507

Histogram contrast analysis and the visual segregation of IID textures.

PubMed

Chubb, C; Econopouly, J; Landy, M S

1994-09-01

A new psychophysical methodology is introduced, histogram contrast analysis, that allows one to measure stimulus transformations, f, used by the visual system to draw distinctions between different image regions. The method involves the discrimination of images constructed by selecting texture micropatterns randomly and independently (across locations) on the basis of a given micropattern histogram. Different components of f are measured by use of different component functions to modulate the micropattern histogram until the resulting textures are discriminable. When no discrimination threshold can be obtained for a given modulating component function, a second titration technique may be used to measure the contribution of that component to f. The method includes several strong tests of its own assumptions. An example is given of the method applied to visual textures composed of small, uniform squares with randomly chosen gray levels. In particular, for a fixed mean gray level mu and a fixed gray-level variance sigma 2, histogram contrast analysis is used to establish that the class S of all textures composed of small squares with jointly independent, identically distributed gray levels with mean mu and variance sigma 2 is perceptually elementary in the following sense: there exists a single, real-valued function f S of gray level, such that two textures I and J in S are discriminable only if the average value of f S applied to the gray levels in I is significantly different from the average value of f S applied to the gray levels in J. Finally, histogram contrast analysis is used to obtain a seventh-order polynomial approximation of f S.

Insight on AV-45 binding in white and grey matter from histogram analysis: a study on early Alzheimer's disease patients and healthy subjects

PubMed Central

Nemmi, Federico; Saint-Aubert, Laure; Adel, Djilali; Salabert, Anne-Sophie; Pariente, Jérémie; Barbeau, Emmanuel; Payoux, Pierre; Péran, Patrice

2014-01-01

Purpose AV-45 amyloid biomarker is known to show uptake in white matter in patients with Alzheimer’s disease (AD) but also in healthy population. This binding; thought to be of a non-specific lipophilic nature has not yet been investigated. The aim of this study was to determine the differential pattern of AV-45 binding in healthy and pathological populations in white matter. Methods We recruited 24 patients presenting with AD at early stage and 17 matched, healthy subjects. We used an optimized PET-MRI registration method and an approach based on intensity histogram using several indexes. We compared the results of the intensity histogram analyses with a more canonical approach based on target-to-cerebellum Standard Uptake Value (SUVr) in white and grey matters using MANOVA and discriminant analyses. A cluster analysis on white and grey matter histograms was also performed. Results White matter histogram analysis revealed significant differences between AD and healthy subjects, which were not revealed by SUVr analysis. However, white matter histograms was not decisive to discriminate groups, and indexes based on grey matter only showed better discriminative power than SUVr. The cluster analysis divided our sample in two clusters, showing different uptakes in grey but also in white matter. Conclusion These results demonstrate that AV-45 binding in white matter conveys subtle information not detectable using SUVr approach. Although it is not better than standard SUVr to discriminate AD patients from healthy subjects, this information could reveal white matter modifications. PMID:24573658

Predicting pathologic tumor response to chemoradiotherapy with histogram distances characterizing longitudinal changes in 18F-FDG uptake patterns

PubMed Central

Tan, Shan; Zhang, Hao; Zhang, Yongxue; Chen, Wengen; D’Souza, Warren D.; Lu, Wei

2013-01-01

Purpose: A family of fluorine-18 (18F)-fluorodeoxyglucose (18F-FDG) positron-emission tomography (PET) features based on histogram distances is proposed for predicting pathologic tumor response to neoadjuvant chemoradiotherapy (CRT). These features describe the longitudinal change of FDG uptake distribution within a tumor. Methods: Twenty patients with esophageal cancer treated with CRT plus surgery were included in this study. All patients underwent PET/CT scans before (pre-) and after (post-) CRT. The two scans were first rigidly registered, and the original tumor sites were then manually delineated on the pre-PET/CT by an experienced nuclear medicine physician. Two histograms representing the FDG uptake distribution were extracted from the pre- and the registered post-PET images, respectively, both within the delineated tumor. Distances between the two histograms quantify longitudinal changes in FDG uptake distribution resulting from CRT, and thus are potential predictors of tumor response. A total of 19 histogram distances were examined and compared to both traditional PET response measures and Haralick texture features. Receiver operating characteristic analyses and Mann-Whitney U test were performed to assess their predictive ability. Results: Among all tested histogram distances, seven bin-to-bin and seven crossbin distances outperformed traditional PET response measures using maximum standardized uptake value (AUC = 0.70) or total lesion glycolysis (AUC = 0.80). The seven bin-to-bin distances were: L2 distance (AUC = 0.84), χ2 distance (AUC = 0.83), intersection distance (AUC = 0.82), cosine distance (AUC = 0.83), squared Euclidean distance (AUC = 0.83), L1 distance (AUC = 0.82), and Jeffrey distance (AUC = 0.82). The seven crossbin distances were: quadratic-chi distance (AUC = 0.89), earth mover distance (AUC = 0.86), fast earth mover distance (AUC = 0.86), diffusion distance (AUC = 0.88), Kolmogorov-Smirnov distance (AUC = 0.88), quadratic form distance (AUC = 0.87), and match distance (AUC = 0.84). These crossbin histogram distance features showed slightly higher prediction accuracy than texture features on post-PET images. Conclusions: The results suggest that longitudinal patterns in 18F-FDG uptake characterized using histogram distances provide useful information for predicting the pathologic response of esophageal cancer to CRT. PMID:24089897

[Characteristics of high resolution diffusion weighted imaging apparent diffusion coefficient histogram and its correlations with cancer stages in patients with nasopharyngeal carcinoma].

PubMed

Wang, G J; Wang, Y; Ye, Y; Chen, F; Lu, Y T; Li, S L

2017-11-07

Objective: To investigate the features of apparent diffusion coefficient (ADC) histogram parameters based on entire tumor volume data in high resolution diffusion weighted imaging of nasopharyngeal carcinoma (NPC) and to evaluate its correlations with cancer stages. Methods: This retrospective study included 154 cases of NPC patients[102 males and 52 females, mean age (48±11) years]who had received readout segmentation of long variable echo trains of MRI scan before radiation therapy. The area of tumor was delineated on each section of axial ADC maps to generate ADC histogram by using Image J. ADC histogram of entire tumor along with the histogram parameters-the tumor voxels, ADC(mean), ADC(25%), ADC(50%), ADC(75%), skewness and kurtosis were obtained by merging all sections with SPSS 22.0 software. Intra-observer repeatability was assessed by using intra-class correlation coefficients (ICC). The patients were subdivided into two groups according to cancer volume: small cancer group (<305 voxels, about 2 cm(3)) and large cancer group (≥2 cm(3)). The correlation between ADC histogram parameters and cancer stages was evaluated with Spearman test. Results: The ICC of measuring ADC histogram parameters of tumor voxels, ADC(mean), ADC(25%), ADC(50%), ADC(75%), skewness, kurtosis was 0.938, 0.861, 0.885, 0.838, 0.836, 0.358 and 0.456, respectively. The tumor voxels was positively correlated with T staging ( r =0.368, P <0.05). There were significant differences in tumor voxels among patients with different T stages ( K =22.306, P <0.05). There were significant differences in the ADC(mean), ADC(25%), ADC(50%) among patients with different T stages in the small cancer group( K =8.409, 8.187, 8.699, all P <0.05), and the up-mentioned three indices were positively correlated with T staging ( r =0.221, 0.209, 0.235, all P <0.05). Skewness and kurtosis differed significantly between the groups with different cancer volume( t =-2.987, Z =-3.770, both P <0.05). Conclusion: The tumor volume, tissue uniformity of NPC are important factors affecting ADC and cancer stages, parameters of ADC histogram (ADC(mean), ADC(25%), ADC(50%)) increases with T staging in NPC smaller than 2 cm(3).

A threshold selection method based on edge preserving

NASA Astrophysics Data System (ADS)

Lou, Liantang; Dan, Wei; Chen, Jiaqi

2015-12-01

A method of automatic threshold selection for image segmentation is presented. An optimal threshold is selected in order to preserve edge of image perfectly in image segmentation. The shortcoming of Otsu's method based on gray-level histograms is analyzed. The edge energy function of bivariate continuous function is expressed as the line integral while the edge energy function of image is simulated by discretizing the integral. An optimal threshold method by maximizing the edge energy function is given. Several experimental results are also presented to compare with the Otsu's method.

RAId_aPS: MS/MS Analysis with Multiple Scoring Functions and Spectrum-Specific Statistics

PubMed Central

Alves, Gelio; Ogurtsov, Aleksey Y.; Yu, Yi-Kuo

2010-01-01

Statistically meaningful comparison/combination of peptide identification results from various search methods is impeded by the lack of a universal statistical standard. Providing an -value calibration protocol, we demonstrated earlier the feasibility of translating either the score or heuristic -value reported by any method into the textbook-defined -value, which may serve as the universal statistical standard. This protocol, although robust, may lose spectrum-specific statistics and might require a new calibration when changes in experimental setup occur. To mitigate these issues, we developed a new MS/MS search tool, RAId_aPS, that is able to provide spectrum-specific -values for additive scoring functions. Given a selection of scoring functions out of RAId score, K-score, Hyperscore and XCorr, RAId_aPS generates the corresponding score histograms of all possible peptides using dynamic programming. Using these score histograms to assign -values enables a calibration-free protocol for accurate significance assignment for each scoring function. RAId_aPS features four different modes: (i) compute the total number of possible peptides for a given molecular mass range, (ii) generate the score histogram given a MS/MS spectrum and a scoring function, (iii) reassign -values for a list of candidate peptides given a MS/MS spectrum and the scoring functions chosen, and (iv) perform database searches using selected scoring functions. In modes (iii) and (iv), RAId_aPS is also capable of combining results from different scoring functions using spectrum-specific statistics. The web link is http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/raid_aps/index.html. Relevant binaries for Linux, Windows, and Mac OS X are available from the same page. PMID:21103371

Reliability of nine programs of topological predictions and their application to integral membrane channel and carrier proteins.

PubMed

Reddy, Abhinay; Cho, Jaehoon; Ling, Sam; Reddy, Vamsee; Shlykov, Maksim; Saier, Milton H

2014-01-01

We evaluated topological predictions for nine different programs, HMMTOP, TMHMM, SVMTOP, DAS, SOSUI, TOPCONS, PHOBIUS, MEMSAT-SVM (hereinafter referred to as MEMSAT), and SPOCTOPUS. These programs were first evaluated using four large topologically well-defined families of secondary transporters, and the three best programs were further evaluated using topologically more diverse families of channels and carriers. In the initial studies, the order of accuracy was: SPOCTOPUS > MEMSAT > HMMTOP > TOPCONS > PHOBIUS > TMHMM > SVMTOP > DAS > SOSUI. Some families, such as the Sugar Porter Family (2.A.1.1) of the Major Facilitator Superfamily (MFS; TC #2.A.1) and the Amino Acid/Polyamine/Organocation (APC) Family (TC #2.A.3), were correctly predicted with high accuracy while others, such as the Mitochondrial Carrier (MC) (TC #2.A.29) and the K(+) transporter (Trk) families (TC #2.A.38), were predicted with much lower accuracy. For small, topologically homogeneous families, SPOCTOPUS and MEMSAT were generally most reliable, while with large, more diverse superfamilies, HMMTOP often proved to have the greatest prediction accuracy. We next developed a novel program, TM-STATS, that tabulates HMMTOP, SPOCTOPUS or MEMSAT-based topological predictions for any subdivision (class, subclass, superfamily, family, subfamily, or any combination of these) of the Transporter Classification Database (TCDB; www.tcdb.org) and examined the following subclasses: α-type channel proteins (TC subclasses 1.A and 1.E), secreted pore-forming toxins (TC subclass 1.C) and secondary carriers (subclass 2.A). Histograms were generated for each of these subclasses, and the results were analyzed according to subclass, family and protein. The results provide an update of topological predictions for integral membrane transport proteins as well as guides for the development of more reliable topological prediction programs, taking family-specific characteristics into account. © 2014 S. Karger AG, Basel.

Microbubble cloud characterization by nonlinear frequency mixing.

PubMed

Cavaro, M; Payan, C; Moysan, J; Baqué, F

2011-05-01

In the frame of the fourth generation forum, France decided to develop sodium fast nuclear reactors. French Safety Authority requests the associated monitoring of argon gas into sodium. This implies to estimate the void fraction, and a histogram indicating the bubble population. In this context, the present letter studies the possibility of achieving an accurate determination of the histogram with acoustic methods. A nonlinear, two-frequency mixing technique has been implemented, and a specific optical device has been developed in order to validate the experimental results. The acoustically reconstructed histograms are in excellent agreement with those obtained using optical methods.

The ISI distribution of the stochastic Hodgkin-Huxley neuron.

PubMed

Rowat, Peter F; Greenwood, Priscilla E

2014-01-01

The simulation of ion-channel noise has an important role in computational neuroscience. In recent years several approximate methods of carrying out this simulation have been published, based on stochastic differential equations, and all giving slightly different results. The obvious, and essential, question is: which method is the most accurate and which is most computationally efficient? Here we make a contribution to the answer. We compare interspike interval histograms from simulated data using four different approximate stochastic differential equation (SDE) models of the stochastic Hodgkin-Huxley neuron, as well as the exact Markov chain model simulated by the Gillespie algorithm. One of the recent SDE models is the same as the Kurtz approximation first published in 1978. All the models considered give similar ISI histograms over a wide range of deterministic and stochastic input. Three features of these histograms are an initial peak, followed by one or more bumps, and then an exponential tail. We explore how these features depend on deterministic input and on level of channel noise, and explain the results using the stochastic dynamics of the model. We conclude with a rough ranking of the four SDE models with respect to the similarity of their ISI histograms to the histogram of the exact Markov chain model.

Histogram equalization with Bayesian estimation for noise robust speech recognition.

PubMed

Suh, Youngjoo; Kim, Hoirin

2018-02-01

The histogram equalization approach is an efficient feature normalization technique for noise robust automatic speech recognition. However, it suffers from performance degradation when some fundamental conditions are not satisfied in the test environment. To remedy these limitations of the original histogram equalization methods, class-based histogram equalization approach has been proposed. Although this approach showed substantial performance improvement under noise environments, it still suffers from performance degradation due to the overfitting problem when test data are insufficient. To address this issue, the proposed histogram equalization technique employs the Bayesian estimation method in the test cumulative distribution function estimation. It was reported in a previous study conducted on the Aurora-4 task that the proposed approach provided substantial performance gains in speech recognition systems based on the acoustic modeling of the Gaussian mixture model-hidden Markov model. In this work, the proposed approach was examined in speech recognition systems with deep neural network-hidden Markov model (DNN-HMM), the current mainstream speech recognition approach where it also showed meaningful performance improvement over the conventional maximum likelihood estimation-based method. The fusion of the proposed features with the mel-frequency cepstral coefficients provided additional performance gains in DNN-HMM systems, which otherwise suffer from performance degradation in the clean test condition.

Dynamic Contrast-enhanced MR Imaging in Renal Cell Carcinoma: Reproducibility of Histogram Analysis on Pharmacokinetic Parameters

PubMed Central

Wang, Hai-yi; Su, Zi-hua; Xu, Xiao; Sun, Zhi-peng; Duan, Fei-xue; Song, Yuan-yuan; Li, Lu; Wang, Ying-wei; Ma, Xin; Guo, Ai-tao; Ma, Lin; Ye, Hui-yi

2016-01-01

Pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) have been increasingly used to evaluate the permeability of tumor vessel. Histogram metrics are a recognized promising method of quantitative MR imaging that has been recently introduced in analysis of DCE-MRI pharmacokinetic parameters in oncology due to tumor heterogeneity. In this study, 21 patients with renal cell carcinoma (RCC) underwent paired DCE-MRI studies on a 3.0 T MR system. Extended Tofts model and population-based arterial input function were used to calculate kinetic parameters of RCC tumors. Mean value and histogram metrics (Mode, Skewness and Kurtosis) of each pharmacokinetic parameter were generated automatically using ImageJ software. Intra- and inter-observer reproducibility and scan–rescan reproducibility were evaluated using intra-class correlation coefficients (ICCs) and coefficient of variation (CoV). Our results demonstrated that the histogram method (Mode, Skewness and Kurtosis) was not superior to the conventional Mean value method in reproducibility evaluation on DCE-MRI pharmacokinetic parameters (K trans & Ve) in renal cell carcinoma, especially for Skewness and Kurtosis which showed lower intra-, inter-observer and scan-rescan reproducibility than Mean value. Our findings suggest that additional studies are necessary before wide incorporation of histogram metrics in quantitative analysis of DCE-MRI pharmacokinetic parameters. PMID:27380733

Evaluation of thresholding techniques for segmenting scaffold images in tissue engineering

NASA Astrophysics Data System (ADS)

Rajagopalan, Srinivasan; Yaszemski, Michael J.; Robb, Richard A.

2004-05-01

Tissue engineering attempts to address the ever widening gap between the demand and supply of organ and tissue transplants using natural and biomimetic scaffolds. The regeneration of specific tissues aided by synthetic materials is dependent on the structural and morphometric properties of the scaffold. These properties can be derived non-destructively using quantitative analysis of high resolution microCT scans of scaffolds. Thresholding of the scanned images into polymeric and porous phase is central to the outcome of the subsequent structural and morphometric analysis. Visual thresholding of scaffolds produced using stochastic processes is inaccurate. Depending on the algorithmic assumptions made, automatic thresholding might also be inaccurate. Hence there is a need to analyze the performance of different techniques and propose alternate ones, if needed. This paper provides a quantitative comparison of different thresholding techniques for segmenting scaffold images. The thresholding algorithms examined include those that exploit spatial information, locally adaptive characteristics, histogram entropy information, histogram shape information, and clustering of gray-level information. The performance of different techniques was evaluated using established criteria, including misclassification error, edge mismatch, relative foreground error, and region non-uniformity. Algorithms that exploit local image characteristics seem to perform much better than those using global information.

Wood texture classification by fuzzy neural networks

NASA Astrophysics Data System (ADS)

Gonzaga, Adilson; de Franca, Celso A.; Frere, Annie F.

1999-03-01

The majority of scientific papers focusing on wood classification for pencil manufacturing take into account defects and visual appearance. Traditional methodologies are base don texture analysis by co-occurrence matrix, by image modeling, or by tonal measures over the plate surface. In this work, we propose to classify plates of wood without biological defects like insect holes, nodes, and cracks, by analyzing their texture. By this methodology we divide the plate image in several rectangular windows or local areas and reduce the number of gray levels. From each local area, we compute the histogram of difference sand extract texture features, given them as input to a Local Neuro-Fuzzy Network. Those features are from the histogram of differences instead of the image pixels due to their better performance and illumination independence. Among several features like media, contrast, second moment, entropy, and IDN, the last three ones have showed better results for network training. Each LNN output is taken as input to a Partial Neuro-Fuzzy Network (PNFN) classifying a pencil region on the plate. At last, the outputs from the PNFN are taken as input to a Global Fuzzy Logic doing the plate classification. Each pencil classification within the plate is done taking into account each quality index.

Approximate Algorithms for Computing Spatial Distance Histograms with Accuracy Guarantees

PubMed Central

Grupcev, Vladimir; Yuan, Yongke; Tu, Yi-Cheng; Huang, Jin; Chen, Shaoping; Pandit, Sagar; Weng, Michael

2014-01-01

Particle simulation has become an important research tool in many scientific and engineering fields. Data generated by such simulations impose great challenges to database storage and query processing. One of the queries against particle simulation data, the spatial distance histogram (SDH) query, is the building block of many high-level analytics, and requires quadratic time to compute using a straightforward algorithm. Previous work has developed efficient algorithms that compute exact SDHs. While beating the naive solution, such algorithms are still not practical in processing SDH queries against large-scale simulation data. In this paper, we take a different path to tackle this problem by focusing on approximate algorithms with provable error bounds. We first present a solution derived from the aforementioned exact SDH algorithm, and this solution has running time that is unrelated to the system size N. We also develop a mathematical model to analyze the mechanism that leads to errors in the basic approximate algorithm. Our model provides insights on how the algorithm can be improved to achieve higher accuracy and efficiency. Such insights give rise to a new approximate algorithm with improved time/accuracy tradeoff. Experimental results confirm our analysis. PMID:24693210

Implementing a Java Based GUI for RICH Detector Analysis

NASA Astrophysics Data System (ADS)

Lendacky, Andrew; Voloshin, Andrew; Benmokhtar, Fatiha

2016-09-01

The CLAS12 detector at Thomas Jefferson National Accelerator Facility (TJNAF) is undergoing an upgrade. One of the improvements is the addition of a Ring Imaging Cherenkov (RICH) detector to improve particle identification in the 3-8 GeV/c momentum range. Approximately 400 multi anode photomultiplier tubes (MAPMTs) are going to be used to detect Cherenkov Radiation in the single photoelectron spectra (SPS). The SPS of each pixel of all MAPMTs have been fitted to a mathematical model of roughly 45 parameters for 4 HVs, 3 OD. Out of those parameters, 9 can be used to evaluate the PMTs performance and placement in the detector. To help analyze data when the RICH is operational, a GUI application was written in Java using Swing and detector packages from TJNAF. To store and retrieve the data, a MySQL database program was written in Java using the JDBC package. Using the database, the GUI pulls the values and produces histograms and graphs for a selected PMT at a specific HV and OD. The GUI will allow researchers to easily view a PMT's performance and efficiency to help with data analysis and ring reconstruction when the RICH is finished.

Data and animal management software for large-scale phenotype screening.

PubMed

Ching, Keith A; Cooke, Michael P; Tarantino, Lisa M; Lapp, Hilmar

2006-04-01

The mouse N-ethyl-N-nitrosourea (ENU) mutagenesis program at the Genomics Institute of the Novartis Research Foundation (GNF) uses MouseTRACS to analyze phenotype screens and manage animal husbandry. MouseTRACS is a Web-based laboratory informatics system that electronically records and organizes mouse colony operations, prints cage cards, tracks inventory, manages requests, and reports Institutional Animal Care and Use Committee (IACUC) protocol usage. For efficient phenotype screening, MouseTRACS identifies mutants, visualizes data, and maps mutations. It displays and integrates phenotype and genotype data using likelihood odds ratio (LOD) plots of genetic linkage between genotype and phenotype. More detailed mapping intervals show individual single nucleotide polymorphism (SNP) markers in the context of phenotype. In addition, dynamically generated pedigree diagrams and inventory reports linked to screening results summarize the inheritance pattern and the degree of penetrance. MouseTRACS displays screening data in tables and uses standard charts such as box plots, histograms, scatter plots, and customized charts looking at clustered mice or cross pedigree comparisons. In summary, MouseTRACS enables the efficient screening, analysis, and management of thousands of animals to find mutant mice and identify novel gene functions. MouseTRACS is available under an open source license at http://www.mousetracs.sourceforge.net.

[Fundamental frequency analysis - a contribution to the objective examination of the speaking and singing voice (author's transl)].

PubMed

Schultz-Coulon, H J

1975-07-01

The applicability of a newly developed fundamental frequency analyzer to diagnosis in phoniatrics is reviewed. During routine voice examination, the analyzer allows a quick and accurate measurement of fundamental frequency and sound level of the speaking voice, and of vocal range and maximum phonation time. By computing fundamental frequency histograms, the median fundamental frequency and the total pitch range can be better determined and compared. Objective studies of certain technical faculties of the singing voice, which usually are estimated subjectively by the speech therapist, may now be done by means of this analyzer. Several examples demonstrate the differences between correct and incorrect phonation. These studies compare the pitch perturbations during the crescendo and decrescendo of a swell-tone, and show typical traces of staccato, thrill and yodel. Conclusions of the study indicate that fundamental frequency analysis is a valuable supplemental method for objective voice examination.

Lightweight Object Oriented Structure analysis: Tools for building Tools to Analyze Molecular Dynamics Simulations

PubMed Central

Romo, Tod D.; Leioatts, Nicholas; Grossfield, Alan

2014-01-01

LOOS (Lightweight Object-Oriented Structure-analysis) is a C++ library designed to facilitate making novel tools for analyzing molecular dynamics simulations by abstracting out the repetitive tasks, allowing developers to focus on the scientifically relevant part of the problem. LOOS supports input using the native file formats of most common biomolecular simulation packages, including CHARMM, NAMD, Amber, Tinker, and Gromacs. A dynamic atom selection language based on the C expression syntax is included and is easily accessible to the tool-writer. In addition, LOOS is bundled with over 120 pre-built tools, including suites of tools for analyzing simulation convergence, 3D histograms, and elastic network models. Through modern C++ design, LOOS is both simple to develop with (requiring knowledge of only 4 core classes and a few utility functions) and is easily extensible. A python interface to the core classes is also provided, further facilitating tool development. PMID:25327784

Lightweight object oriented structure analysis: tools for building tools to analyze molecular dynamics simulations.

PubMed

Romo, Tod D; Leioatts, Nicholas; Grossfield, Alan

2014-12-15

LOOS (Lightweight Object Oriented Structure-analysis) is a C++ library designed to facilitate making novel tools for analyzing molecular dynamics simulations by abstracting out the repetitive tasks, allowing developers to focus on the scientifically relevant part of the problem. LOOS supports input using the native file formats of most common biomolecular simulation packages, including CHARMM, NAMD, Amber, Tinker, and Gromacs. A dynamic atom selection language based on the C expression syntax is included and is easily accessible to the tool-writer. In addition, LOOS is bundled with over 140 prebuilt tools, including suites of tools for analyzing simulation convergence, three-dimensional histograms, and elastic network models. Through modern C++ design, LOOS is both simple to develop with (requiring knowledge of only four core classes and a few utility functions) and is easily extensible. A python interface to the core classes is also provided, further facilitating tool development. © 2014 Wiley Periodicals, Inc.

Apparent diffusion coefficient histogram analysis can evaluate radiation-induced parotid damage and predict late xerostomia degree in nasopharyngeal carcinoma

PubMed Central

Zhou, Nan; Guo, Tingting; Zheng, Huanhuan; Pan, Xia; Chu, Chen; Dou, Xin; Li, Ming; Liu, Song; Zhu, Lijing; Liu, Baorui; Chen, Weibo; He, Jian; Yan, Jing; Zhou, Zhengyang; Yang, Xiaofeng

2017-01-01

We investigated apparent diffusion coefficient (ADC) histogram analysis to evaluate radiation-induced parotid damage and predict xerostomia degrees in nasopharyngeal carcinoma (NPC) patients receiving radiotherapy. The imaging of bilateral parotid glands in NPC patients was conducted 2 weeks before radiotherapy (time point 1), one month after radiotherapy (time point 2), and four months after radiotherapy (time point 3). From time point 1 to 2, parotid volume, skewness, and kurtosis decreased (P < 0.001, = 0.001, and < 0.001, respectively), but all other ADC histogram parameters increased (all P < 0.001, except P = 0.006 for standard deviation [SD]). From time point 2 to 3, parotid volume continued to decrease (P = 0.022), and SD, 75th and 90th percentiles continued to increase (P = 0.024, 0.010, and 0.006, respectively). Early change rates of parotid ADCmean, ADCmin, kurtosis, and 25th, 50th, 75th, 90th percentiles (from time point 1 to 2) correlated with late parotid atrophy rate (from time point 1 to 3) (all P < 0.05). Multiple linear regression analysis revealed correlations among parotid volume, time point, and ADC histogram parameters. Early mean change rates for bilateral parotid SD and ADCmax could predict late xerostomia degrees at seven months after radiotherapy (three months after time point 3) with AUC of 0.781 and 0.818 (P = 0.014, 0.005, respectively). ADC histogram parameters were reproducible (intraclass correlation coefficient, 0.830 - 0.999). ADC histogram analysis could be used to evaluate radiation-induced parotid damage noninvasively, and predict late xerostomia degrees of NPC patients treated with radiotherapy. PMID:29050274

Correlation of histogram analysis of apparent diffusion coefficient with uterine cervical pathologic finding.

PubMed

Lin, Yuning; Li, Hui; Chen, Ziqian; Ni, Ping; Zhong, Qun; Huang, Huijuan; Sandrasegaran, Kumar

2015-05-01

The purpose of this study was to investigate the application of histogram analysis of apparent diffusion coefficient (ADC) in characterizing pathologic features of cervical cancer and benign cervical lesions. This prospective study was approved by the institutional review board, and written informed consent was obtained. Seventy-three patients with cervical cancer (33-69 years old; 35 patients with International Federation of Gynecology and Obstetrics stage IB cervical cancer) and 38 patients (38-61 years old) with normal cervix or cervical benign lesions (control group) were enrolled. All patients underwent 3-T diffusion-weighted imaging (DWI) with b values of 0 and 800 s/mm(2). ADC values of the entire tumor in the patient group and the whole cervix volume in the control group were assessed. Mean ADC, median ADC, 25th and 75th percentiles of ADC, skewness, and kurtosis were calculated. Histogram parameters were compared between different pathologic features, as well as between stage IB cervical cancer and control groups. Mean ADC, median ADC, and 25th percentile of ADC were significantly higher for adenocarcinoma (p = 0.021, 0.006, and 0.004, respectively), and skewness was significantly higher for squamous cell carcinoma (p = 0.011). Median ADC was statistically significantly higher for well or moderately differentiated tumors (p = 0.044), and skewness was statistically significantly higher for poorly differentiated tumors (p = 0.004). No statistically significant difference of ADC histogram was observed between lymphovascular space invasion subgroups. All histogram parameters differed significantly between stage IB cervical cancer and control groups (p < 0.05). Distribution of ADCs characterized by histogram analysis may help to distinguish early-stage cervical cancer from normal cervix or cervical benign lesions and may be useful for evaluating the different pathologic features of cervical cancer.

Differentiating between Glioblastoma and Primary CNS Lymphoma Using Combined Whole-tumor Histogram Analysis of the Normalized Cerebral Blood Volume and the Apparent Diffusion Coefficient.

PubMed

Bao, Shixing; Watanabe, Yoshiyuki; Takahashi, Hiroto; Tanaka, Hisashi; Arisawa, Atsuko; Matsuo, Chisato; Wu, Rongli; Fujimoto, Yasunori; Tomiyama, Noriyuki

2018-05-31

This study aimed to determine whether whole-tumor histogram analysis of normalized cerebral blood volume (nCBV) and apparent diffusion coefficient (ADC) for contrast-enhancing lesions can be used to differentiate between glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL). From 20 patients, 9 with PCNSL and 11 with GBM without any hemorrhagic lesions, underwent MRI, including diffusion-weighted imaging and dynamic susceptibility contrast perfusion-weighted imaging before surgery. Histogram analysis of nCBV and ADC from whole-tumor voxels in contrast-enhancing lesions was performed. An unpaired t-test was used to compare the mean values for each type of tumor. A multivariate logistic regression model (LRM) was performed to classify GBM and PCNSL using the best parameters of ADC and nCBV. All nCBV histogram parameters of GBMs were larger than those of PCNSLs, but only average nCBV was statistically significant after Bonferroni correction. Meanwhile, ADC histogram parameters were also larger in GBM compared to those in PCNSL, but these differences were not statistically significant. According to receiver operating characteristic curve analysis, the nCBV average and ADC 25th percentile demonstrated the largest area under the curve with values of 0.869 and 0.838, respectively. The LRM combining these two parameters differentiated between GBM and PCNSL with a higher area under the curve value (Logit (P) = -21.12 + 10.00 × ADC 25th percentile (10 -3 mm 2 /s) + 5.420 × nCBV mean, P < 0.001). Our results suggest that whole-tumor histogram analysis of nCBV and ADC combined can be a valuable objective diagnostic method for differentiating between GBM and PCNSL.

Histogram analysis of diffusion kurtosis imaging estimates for in vivo assessment of 2016 WHO glioma grades: A cross-sectional observational study.

PubMed

Hempel, Johann-Martin; Schittenhelm, Jens; Brendle, Cornelia; Bender, Benjamin; Bier, Georg; Skardelly, Marco; Tabatabai, Ghazaleh; Castaneda Vega, Salvador; Ernemann, Ulrike; Klose, Uwe

2017-10-01

To assess the diagnostic performance of histogram analysis of diffusion kurtosis imaging (DKI) maps for in vivo assessment of the 2016 World Health Organization Classification of Tumors of the Central Nervous System (2016 CNS WHO) integrated glioma grades. Seventy-seven patients with histopathologically-confirmed glioma who provided written informed consent were retrospectively assessed between 01/2014 and 03/2017 from a prospective trial approved by the local institutional review board. Ten histogram parameters of mean kurtosis (MK) and mean diffusivity (MD) metrics from DKI were independently assessed by two blinded physicians from a volume of interest around the entire solid tumor. One-way ANOVA was used to compare MK and MD histogram parameter values between 2016 CNS WHO-based tumor grades. Receiver operating characteristic analysis was performed on MK and MD histogram parameters for significant results. The 25th, 50th, 75th, and 90th percentiles of MK and average MK showed significant differences between IDH1/2 wild-type gliomas, IDH1/2 mutated gliomas, and oligodendrogliomas with chromosome 1p/19q loss of heterozygosity and IDH1/2 mutation (p<0.001). The 50th, 75th, and 90th percentiles showed a slightly higher diagnostic performance (area under the curve (AUC) range; 0.868-0.991) than average MK (AUC range; 0.855-0.988) in classifying glioma according to the integrated approach of 2016 CNS WHO. Histogram analysis of DKI can stratify gliomas according to the integrated approach of 2016 CNS WHO. The 50th (median), 75th , and the 90th percentiles showed the highest diagnostic performance. However, the average MK is also robust and feasible in routine clinical practice. Copyright © 2017 Elsevier B.V. All rights reserved.

Apparent diffusion coefficient histogram analysis can evaluate radiation-induced parotid damage and predict late xerostomia degree in nasopharyngeal carcinoma.

PubMed

Zhou, Nan; Guo, Tingting; Zheng, Huanhuan; Pan, Xia; Chu, Chen; Dou, Xin; Li, Ming; Liu, Song; Zhu, Lijing; Liu, Baorui; Chen, Weibo; He, Jian; Yan, Jing; Zhou, Zhengyang; Yang, Xiaofeng

2017-09-19

We investigated apparent diffusion coefficient (ADC) histogram analysis to evaluate radiation-induced parotid damage and predict xerostomia degrees in nasopharyngeal carcinoma (NPC) patients receiving radiotherapy. The imaging of bilateral parotid glands in NPC patients was conducted 2 weeks before radiotherapy (time point 1), one month after radiotherapy (time point 2), and four months after radiotherapy (time point 3). From time point 1 to 2, parotid volume, skewness, and kurtosis decreased ( P < 0.001, = 0.001, and < 0.001, respectively), but all other ADC histogram parameters increased (all P < 0.001, except P = 0.006 for standard deviation [SD]). From time point 2 to 3, parotid volume continued to decrease ( P = 0.022), and SD, 75 th and 90 th percentiles continued to increase ( P = 0.024, 0.010, and 0.006, respectively). Early change rates of parotid ADC mean , ADC min , kurtosis, and 25 th , 50 th , 75 th , 90 th percentiles (from time point 1 to 2) correlated with late parotid atrophy rate (from time point 1 to 3) (all P < 0.05). Multiple linear regression analysis revealed correlations among parotid volume, time point, and ADC histogram parameters. Early mean change rates for bilateral parotid SD and ADC max could predict late xerostomia degrees at seven months after radiotherapy (three months after time point 3) with AUC of 0.781 and 0.818 ( P = 0.014, 0.005, respectively). ADC histogram parameters were reproducible (intraclass correlation coefficient, 0.830 - 0.999). ADC histogram analysis could be used to evaluate radiation-induced parotid damage noninvasively, and predict late xerostomia degrees of NPC patients treated with radiotherapy.

Comparison between types I and II epithelial ovarian cancer using histogram analysis of monoexponential, biexponential, and stretched-exponential diffusion models.

PubMed

Wang, Feng; Wang, Yuxiang; Zhou, Yan; Liu, Congrong; Xie, Lizhi; Zhou, Zhenyu; Liang, Dong; Shen, Yang; Yao, Zhihang; Liu, Jianyu

2017-12-01

To evaluate the utility of histogram analysis of monoexponential, biexponential, and stretched-exponential models to a dualistic model of epithelial ovarian cancer (EOC). Fifty-two patients with histopathologically proven EOC underwent preoperative magnetic resonance imaging (MRI) (including diffusion-weighted imaging [DWI] with 11 b-values) using a 3.0T system and were divided into two groups: types I and II. Apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α) histograms were obtained based on solid components of the entire tumor. The following metrics of each histogram were compared between two types: 1) mean; 2) median; 3) 10th percentile and 90th percentile. Conventional MRI morphological features were also recorded. Significant morphological features for predicting EOC type were maximum diameter (P = 0.007), texture of lesion (P = 0.001), and peritoneal implants (P = 0.001). For ADC, D, f, DDC, and α, all metrics were significantly lower in type II than type I (P < 0.05). Mean, median, 10th, and 90th percentile of D* were not significantly different (P = 0.336, 0.154, 0.779, and 0.203, respectively). Most histogram metrics of ADC, D, and DDC had significantly higher area under the receiver operating characteristic curve values than those of f and α (P < 0.05) CONCLUSION: It is feasible to grade EOC by morphological features and three models with histogram analysis. ADC, D, and DDC have better performance than f and α; f and α may provide additional information. 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1797-1809. © 2017 International Society for Magnetic Resonance in Medicine.

Principal component analysis of the CT density histogram to generate parametric response maps of COPD

NASA Astrophysics Data System (ADS)

Zha, N.; Capaldi, D. P. I.; Pike, D.; McCormack, D. G.; Cunningham, I. A.; Parraga, G.

2015-03-01

Pulmonary x-ray computed tomography (CT) may be used to characterize emphysema and airways disease in patients with chronic obstructive pulmonary disease (COPD). One analysis approach - parametric response mapping (PMR) utilizes registered inspiratory and expiratory CT image volumes and CT-density-histogram thresholds, but there is no consensus regarding the threshold values used, or their clinical meaning. Principal-component-analysis (PCA) of the CT density histogram can be exploited to quantify emphysema using data-driven CT-density-histogram thresholds. Thus, the objective of this proof-of-concept demonstration was to develop a PRM approach using PCA-derived thresholds in COPD patients and ex-smokers without airflow limitation. Methods: Fifteen COPD ex-smokers and 5 normal ex-smokers were evaluated. Thoracic CT images were also acquired at full inspiration and full expiration and these images were non-rigidly co-registered. PCA was performed for the CT density histograms, from which the components with the highest eigenvalues greater than one were summed. Since the values of the principal component curve correlate directly with the variability in the sample, the maximum and minimum points on the curve were used as threshold values for the PCA-adjusted PRM technique. Results: A significant correlation was determined between conventional and PCA-adjusted PRM with 3He MRI apparent diffusion coefficient (p<0.001), with CT RA950 (p<0.0001), as well as with 3He MRI ventilation defect percent, a measurement of both small airways disease (p=0.049 and p=0.06, respectively) and emphysema (p=0.02). Conclusions: PRM generated using PCA thresholds of the CT density histogram showed significant correlations with CT and 3He MRI measurements of emphysema, but not airways disease.

TH-E-BRF-09: Gaussian Mixture Model Analysis of Radiation-Induced Parotid-Gland Injury: An Ultrasound Study of Acute and Late Xerostomia in Head-And-Neck Radiotherapy

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

Liu, T; Yu, D; Beitler, J

Purpose: Xerostomia (dry mouth), secondary to parotid-gland injury, is a distressing side-effect in head-and-neck radiotherapy (RT). This study's purpose is to develop a novel ultrasound technique to quantitatively evaluate post-RT parotid-gland injury. Methods: Recent ultrasound studies have shown that healthy parotid glands exhibit homogeneous echotexture, whereas post-RT parotid glands are often heterogeneous, with multiple hypoechoic (inflammation) or hyperechoic (fibrosis) regions. We propose to use a Gaussian mixture model to analyze the ultrasonic echo-histogram of the parotid glands. An IRB-approved clinical study was conducted: (1) control-group: 13 healthy-volunteers, served as the control; (2) acutetoxicity group − 20 patients (mean age: 62.5more » ± 8.9 years, follow-up: 2.0±0.8 months); and (3) late-toxicity group − 18 patients (mean age: 60.7 ± 7.3 years, follow-up: 20.1±10.4 months). All patients experienced RTOG grade 1 or 2 salivary-gland toxicity. Each participant underwent an ultrasound scan (10 MHz) of the bilateral parotid glands. An echo-intensity histogram was derived for each parotid and a Gaussian mixture model was used to fit the histogram using expectation maximization (EM) algorithm. The quality of the fitting was evaluated with the R-squared value. Results: (1) Controlgroup: all parotid glands fitted well with one Gaussian component, with a mean intensity of 79.8±4.9 (R-squared>0.96). (2) Acute-toxicity group: 37 of the 40 post-RT parotid glands fitted well with two Gaussian components, with a mean intensity of 42.9±7.4, 73.3±12.2 (R-squared>0.95). (3) Latetoxicity group: 32 of the 36 post-RT parotid fitted well with 3 Gaussian components, with mean intensities of 49.7±7.6, 77.2±8.7, and 118.6±11.8 (R-squared>0.98). Conclusion: RT-associated parotid-gland injury is common in head-and-neck RT, but challenging to assess. This work has demonstrated that the Gaussian mixture model of the echo-histogram could quantify acute and late toxicity of the parotid glands. This study provides meaningful preliminary data from future observational and interventional clinical research.« less

Local intensity area descriptor for facial recognition in ideal and noise conditions

NASA Astrophysics Data System (ADS)

Tran, Chi-Kien; Tseng, Chin-Dar; Chao, Pei-Ju; Ting, Hui-Min; Chang, Liyun; Huang, Yu-Jie; Lee, Tsair-Fwu

2017-03-01

We propose a local texture descriptor, local intensity area descriptor (LIAD), which is applied for human facial recognition in ideal and noisy conditions. Each facial image is divided into small regions from which LIAD histograms are extracted and concatenated into a single feature vector to represent the facial image. The recognition is performed using a nearest neighbor classifier with histogram intersection and chi-square statistics as dissimilarity measures. Experiments were conducted with LIAD using the ORL database of faces (Olivetti Research Laboratory, Cambridge), the Face94 face database, the Georgia Tech face database, and the FERET database. The results demonstrated the improvement in accuracy of our proposed descriptor compared to conventional descriptors [local binary pattern (LBP), uniform LBP, local ternary pattern, histogram of oriented gradients, and local directional pattern]. Moreover, the proposed descriptor was less sensitive to noise and had low histogram dimensionality. Thus, it is expected to be a powerful texture descriptor that can be used for various computer vision problems.

A Comparative Study on Preprocessing Techniques in Diabetic Retinopathy Retinal Images: Illumination Correction and Contrast Enhancement

PubMed Central

Rasta, Seyed Hossein; Partovi, Mahsa Eisazadeh; Seyedarabi, Hadi; Javadzadeh, Alireza

2015-01-01

To investigate the effect of preprocessing techniques including contrast enhancement and illumination correction on retinal image quality, a comparative study was carried out. We studied and implemented a few illumination correction and contrast enhancement techniques on color retinal images to find out the best technique for optimum image enhancement. To compare and choose the best illumination correction technique we analyzed the corrected red and green components of color retinal images statistically and visually. The two contrast enhancement techniques were analyzed using a vessel segmentation algorithm by calculating the sensitivity and specificity. The statistical evaluation of the illumination correction techniques were carried out by calculating the coefficients of variation. The dividing method using the median filter to estimate background illumination showed the lowest Coefficients of variations in the red component. The quotient and homomorphic filtering methods after the dividing method presented good results based on their low Coefficients of variations. The contrast limited adaptive histogram equalization increased the sensitivity of the vessel segmentation algorithm up to 5% in the same amount of accuracy. The contrast limited adaptive histogram equalization technique has a higher sensitivity than the polynomial transformation operator as a contrast enhancement technique for vessel segmentation. Three techniques including the dividing method using the median filter to estimate background, quotient based and homomorphic filtering were found as the effective illumination correction techniques based on a statistical evaluation. Applying the local contrast enhancement technique, such as CLAHE, for fundus images presented good potentials in enhancing the vasculature segmentation. PMID:25709940

A Bayesian Modeling Approach for Estimation of a Shape-Free Groundwater Age Distribution using Multiple Tracers

DOE PAGES

Massoudieh, Arash; Visser, Ate; Sharifi, Soroosh; ...

2013-10-15

The mixing of groundwaters with different ages in aquifers, groundwater age is more appropriately represented by a distribution rather than a scalar number. To infer a groundwater age distribution from environmental tracers, a mathematical form is often assumed for the shape of the distribution and the parameters of the mathematical distribution are estimated using deterministic or stochastic inverse methods. We found that the prescription of the mathematical form limits the exploration of the age distribution to the shapes that can be described by the selected distribution. In this paper, the use of freeform histograms as groundwater age distributions is evaluated.more » A Bayesian Markov Chain Monte Carlo approach is used to estimate the fraction of groundwater in each histogram bin. This method was able to capture the shape of a hypothetical gamma distribution from the concentrations of four age tracers. The number of bins that can be considered in this approach is limited based on the number of tracers available. The histogram method was also tested on tracer data sets from Holten (The Netherlands; 3H, 3He, 85Kr, 39Ar) and the La Selva Biological Station (Costa-Rica; SF 6, CFCs, 3H, 4He and 14C), and compared to a number of mathematical forms. According to standard Bayesian measures of model goodness, the best mathematical distribution performs better than the histogram distributions in terms of the ability to capture the observed tracer data relative to their complexity. Among the histogram distributions, the four bin histogram performs better in most of the cases. The Monte Carlo simulations showed strong correlations in the posterior estimates of bin contributions, indicating that these bins cannot be well constrained using the available age tracers. The fact that mathematical forms overall perform better than the freeform histogram does not undermine the benefit of the freeform approach, especially for the cases where a larger amount of observed data is available and when the real groundwater distribution is more complex than can be represented by simple mathematical forms.« less

A Bayesian Modeling Approach for Estimation of a Shape-Free Groundwater Age Distribution using Multiple Tracers

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

Massoudieh, Arash; Visser, Ate; Sharifi, Soroosh

The mixing of groundwaters with different ages in aquifers, groundwater age is more appropriately represented by a distribution rather than a scalar number. To infer a groundwater age distribution from environmental tracers, a mathematical form is often assumed for the shape of the distribution and the parameters of the mathematical distribution are estimated using deterministic or stochastic inverse methods. We found that the prescription of the mathematical form limits the exploration of the age distribution to the shapes that can be described by the selected distribution. In this paper, the use of freeform histograms as groundwater age distributions is evaluated.more » A Bayesian Markov Chain Monte Carlo approach is used to estimate the fraction of groundwater in each histogram bin. This method was able to capture the shape of a hypothetical gamma distribution from the concentrations of four age tracers. The number of bins that can be considered in this approach is limited based on the number of tracers available. The histogram method was also tested on tracer data sets from Holten (The Netherlands; 3H, 3He, 85Kr, 39Ar) and the La Selva Biological Station (Costa-Rica; SF 6, CFCs, 3H, 4He and 14C), and compared to a number of mathematical forms. According to standard Bayesian measures of model goodness, the best mathematical distribution performs better than the histogram distributions in terms of the ability to capture the observed tracer data relative to their complexity. Among the histogram distributions, the four bin histogram performs better in most of the cases. The Monte Carlo simulations showed strong correlations in the posterior estimates of bin contributions, indicating that these bins cannot be well constrained using the available age tracers. The fact that mathematical forms overall perform better than the freeform histogram does not undermine the benefit of the freeform approach, especially for the cases where a larger amount of observed data is available and when the real groundwater distribution is more complex than can be represented by simple mathematical forms.« less

Gliomas: Application of Cumulative Histogram Analysis of Normalized Cerebral Blood Volume on 3 T MRI to Tumor Grading

PubMed Central

Kim, Hyungjin; Choi, Seung Hong; Kim, Ji-Hoon; Ryoo, Inseon; Kim, Soo Chin; Yeom, Jeong A.; Shin, Hwaseon; Jung, Seung Chai; Lee, A. Leum; Yun, Tae Jin; Park, Chul-Kee; Sohn, Chul-Ho; Park, Sung-Hye

2013-01-01

Background Glioma grading assumes significant importance in that low- and high-grade gliomas display different prognoses and are treated with dissimilar therapeutic strategies. The objective of our study was to retrospectively assess the usefulness of a cumulative normalized cerebral blood volume (nCBV) histogram for glioma grading based on 3 T MRI. Methods From February 2010 to April 2012, 63 patients with astrocytic tumors underwent 3 T MRI with dynamic susceptibility contrast perfusion-weighted imaging. Regions of interest containing the entire tumor volume were drawn on every section of the co-registered relative CBV (rCBV) maps and T2-weighted images. The percentile values from the cumulative nCBV histograms and the other histogram parameters were correlated with tumor grades. Cochran’s Q test and the McNemar test were used to compare the diagnostic accuracies of the histogram parameters after the receiver operating characteristic curve analysis. Using the parameter offering the highest diagnostic accuracy, a validation process was performed with an independent test set of nine patients. Results The 99th percentile of the cumulative nCBV histogram (nCBV C99), mean and peak height differed significantly between low- and high-grade gliomas (P = <0.001, 0.014 and <0.001, respectively) and between grade III and IV gliomas (P = <0.001, 0.001 and <0.001, respectively). The diagnostic accuracy of nCBV C99 was significantly higher than that of the mean nCBV (P = 0.016) in distinguishing high- from low-grade gliomas and was comparable to that of the peak height (P = 1.000). Validation using the two cutoff values of nCBV C99 achieved a diagnostic accuracy of 66.7% (6/9) for the separation of all three glioma grades. Conclusion Cumulative histogram analysis of nCBV using 3 T MRI can be a useful method for preoperative glioma grading. The nCBV C99 value is helpful in distinguishing high- from low-grade gliomas and grade IV from III gliomas. PMID:23704910

Comparison of Utility of Histogram Apparent Diffusion Coefficient and R2* for Differentiation of Low-Grade From High-Grade Clear Cell Renal Cell Carcinoma.

PubMed

Zhang, Yu-Dong; Wu, Chen-Jiang; Wang, Qing; Zhang, Jing; Wang, Xiao-Ning; Liu, Xi-Sheng; Shi, Hai-Bin

2015-08-01

The purpose of this study was to compare histogram analysis of apparent diffusion coefficient (ADC) and R2* for differentiating low-grade from high-grade clear cell renal cell carcinoma (RCC). Forty-six patients with pathologically confirmed clear cell RCC underwent preoperative BOLD and DWI MRI of the kidneys. ADCs based on the entire tumor volume were calculated with b value combinations of 0 and 800 s/mm(2). ROI-based R2* was calculated with eight TE combinations of 6.7-22.8 milliseconds. Histogram analysis of tumor ADCs and R2* values was performed to obtain mean; median; width; and fifth, 10th, 90th, and 95th percentiles and histogram inhomogeneity, kurtosis, and skewness for all lesions. Thirty-three low-grade and 13 high-grade clear cell RCCs were found at pathologic examination. The TNM classification and tumor volume of clear cell RCC significantly correlated with histogram ADC and R2* (ρ = -0.317 to 0.506; p < 0.05). High-grade clear cell RCC had significantly lower mean, median, and 10th percentile ADCs but higher inhomogeneity and median R2* than low-grade clear cell RCC (all p < 0.05). Compared with other histogram ADC and R2* indexes, 10th percentile ADC had the highest accuracy (91.3%) in discriminating low- from high-grade clear cell RCC. R2* in discriminating hemorrhage was achieved with a threshold of 68.95 Hz. At this threshold, high-grade clear cell RCC had a significantly higher prevalence of intratumor hemorrhage (high-grade, 76.9%; low-grade, 45.4%; p < 0.05) and larger hemorrhagic area than low-grade clear cell RCC (high-grade, 34.9% ± 31.6%; low-grade, 8.9 ± 16.8%; p < 0.05). A close relation was found between MRI indexes and pathologic findings. Histogram analysis of ADC and R2* allows differentiation of low- from high-grade clear cell RCC with high accuracy.

Histogram analysis of apparent diffusion coefficient maps for assessing thymic epithelial tumours: correlation with world health organization classification and clinical staging.

PubMed

Kong, Ling-Yan; Zhang, Wei; Zhou, Yue; Xu, Hai; Shi, Hai-Bin; Feng, Qing; Xu, Xiao-Quan; Yu, Tong-Fu

2018-04-01

To investigate the value of apparent diffusion coefficients (ADCs) histogram analysis for assessing World Health Organization (WHO) pathological classification and Masaoka clinical stages of thymic epithelial tumours. 37 patients with histologically confirmed thymic epithelial tumours were enrolled. ADC measurements were performed using hot-spot ROI (ADC HS-ROI ) and histogram-based approach. ADC histogram parameters included mean ADC (ADC mean ), median ADC (ADC median ), 10 and 90 percentile of ADC (ADC 10 and ADC 90 ), kurtosis and skewness. One-way ANOVA, independent-sample t-test, and receiver operating characteristic were used for statistical analyses. There were significant differences in ADC mean , ADC median , ADC 10 , ADC 90 and ADC HS-ROI among low-risk thymoma (type A, AB, B1; n = 14), high-risk thymoma (type B2, B3; n = 9) and thymic carcinoma (type C, n = 14) groups (all p-values <0.05), while no significant difference in skewness (p = 0.181) and kurtosis (p = 0.088). ADC 10 showed best differentiating ability (cut-off value, ≤0.689 × 10 -3 mm 2 s -1 ; AUC, 0.957; sensitivity, 95.65%; specificity, 92.86%) for discriminating low-risk thymoma from high-risk thymoma and thymic carcinoma. Advanced Masaoka stages (Stage III and IV; n = 24) tumours showed significant lower ADC parameters and higher kurtosis than early Masaoka stage (Stage I and II; n = 13) tumours (all p-values <0.05), while no significant difference on skewness (p = 0.063). ADC 10 showed best differentiating ability (cut-off value, ≤0.689 × 10 -3 mm 2 s -1 ; AUC, 0.913; sensitivity, 91.30%; specificity, 85.71%) for discriminating advanced and early Masaoka stage epithelial tumours. ADC histogram analysis may assist in assessing the WHO pathological classification and Masaoka clinical stages of thymic epithelial tumours. Advances in knowledge: 1. ADC histogram analysis could help to assess WHO pathological classification of thymic epithelial tumours. 2. ADC histogram analysis could help to evaluate Masaoka clinical stages of thymic epithelial tumours. 3. ADC 10 might be a promising imaging biomarker for assessing and characterizing thymic epithelial tumours.

Utility of whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs).

PubMed

Hoffman, David H; Ream, Justin M; Hajdu, Christina H; Rosenkrantz, Andrew B

2017-04-01

To evaluate whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs), including in comparison with conventional MRI features. Eighteen branch-duct IPMNs underwent MRI with DWI prior to resection (n = 16) or FNA (n = 2). A blinded radiologist placed 3D volumes-of-interest on the entire IPMN on the ADC map, from which whole-lesion histogram metrics were generated. The reader also assessed IPMN size, mural nodularity, and adjacent main-duct dilation. Benign (low-to-intermediate grade dysplasia; n = 10) and malignant (high-grade dysplasia or invasive adenocarcinoma; n = 8) IPMNs were compared. Whole-lesion ADC histogram metrics demonstrating significant differences between benign and malignant IPMNs were: entropy (5.1 ± 0.2 vs. 5.4 ± 0.2; p = 0.01, AUC = 86%); mean of the bottom 10th percentile (2.2 ± 0.4 vs. 1.6 ± 0.7; p = 0.03; AUC = 81%); and mean of the 10-25th percentile (2.8 ± 0.4 vs. 2.3 ± 0.6; p = 0.04; AUC = 79%). The overall mean ADC, skewness, and kurtosis were not significantly different between groups (p ≥ 0.06; AUC = 50-78%). For entropy (highest performing histogram metric), an optimal threshold of >5.3 achieved a sensitivity of 100%, a specificity of 70%, and an accuracy of 83% for predicting malignancy. No significant difference (p = 0.18-0.64) was observed between benign and malignant IPMNs for cyst size ≥3 cm, adjacent main-duct dilatation, or mural nodule. At multivariable analysis of entropy in combination with all other ADC histogram and conventional MRI features, entropy was the only significant independent predictor of malignancy (p = 0.004). Although requiring larger studies, ADC entropy obtained from 3D whole-lesion histogram analysis may serve as a biomarker for identifying the malignant potential of IPMNs, independent of conventional MRI features.

Definition of preclinical and clinical character of human symptomatic status by quasi-elastic light scattering (QELS) investigations of blood plasma

NASA Astrophysics Data System (ADS)

Ivanova, Mariya A.; Klopov, Nicolay V.; Lebedev, Andrei D.; Noskin, Leonid A.; Noskin, Valentin A.; Pavlov, Michail Y.

1997-05-01

We discuss the use of the QELS method for screening of population groups for verified pathologies. For mathematical analysis of experimental data the regularization procedure have been used. This allows us to determine the histograms of particle size distribution of blood plasma samples. For the interpretation of the histogram data the special program of the mathematical processing - 'semiotic classifier' - have been created. The main idea of the 'semiotic classifier' is based on the fact, that formation of the pathological trace in human organism depends not only on concrete disease nature but also on the interaction between the organism sanogenetic mechanisms. We separate five pathological symptomatic complexes of organism status: allergic diseases, intoxications, organism catabolic shifts, auto-immune diseases and degenerative-dystrophy processes. The use of this 'semiotic classifier' in the system of monitoring investigations allows to solve the next problems: (1) to separate the persons with the expressed initial level of pathological processes to the risk groups for the special clinical investigations, (2) to set up the predisposition of the concrete individual towards definite pathologies at the preclinical stage, (3) under the conditions of expressed clinical pathology to study the dynamics of pathology processes.

Histogram-based ionogram displays and their application to autoscaling

NASA Astrophysics Data System (ADS)

Lynn, Kenneth J. W.

2018-03-01

A simple method is described for displaying and auto scaling the basic ionogram parameters foF2 and h'F2 as well as some additional layer parameters from digital ionograms. The technique employed is based on forming frequency and height histograms in each ionogram. This technique has now been applied specifically to ionograms produced by the IPS5D ionosonde developed and operated by the Australian Space Weather Service (SWS). The SWS ionograms are archived in a cleaned format and readily available from the SWS internet site. However, the method is applicable to any ionosonde which produces ionograms in a digital format at a useful signal-to-noise level. The most novel feature of the technique for autoscaling is its simplicity and the avoidance of the mathematical imaging and line fitting techniques often used. The program arose from the necessity to display many days of ionogram output to allow the location of specific types of ionospheric event such as ionospheric storms, travelling ionospheric disturbances and repetitive ionospheric height changes for further investigation and measurement. Examples and applications of the method are given including the removal of sporadic E and spread F.

Very low cost real time histogram-based contrast enhancer utilizing fixed-point DSP processing

NASA Astrophysics Data System (ADS)

McCaffrey, Nathaniel J.; Pantuso, Francis P.

1998-03-01

A real time contrast enhancement system utilizing histogram- based algorithms has been developed to operate on standard composite video signals. This low-cost DSP based system is designed with fixed-point algorithms and an off-chip look up table (LUT) to reduce the cost considerably over other contemporary approaches. This paper describes several real- time contrast enhancing systems advanced at the Sarnoff Corporation for high-speed visible and infrared cameras. The fixed-point enhancer was derived from these high performance cameras. The enhancer digitizes analog video and spatially subsamples the stream to qualify the scene's luminance. Simultaneously, the video is streamed through a LUT that has been programmed with the previous calculation. Reducing division operations by subsampling reduces calculation- cycles and also allows the processor to be used with cameras of nominal resolutions. All values are written to the LUT during blanking so no frames are lost. The enhancer measures 13 cm X 6.4 cm X 3.2 cm, operates off 9 VAC and consumes 12 W. This processor is small and inexpensive enough to be mounted with field deployed security cameras and can be used for surveillance, video forensics and real- time medical imaging.

Sandia PUF Analysis Tool

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

2014-06-11

This program is a graphical user interface for measuring and performing inter-active analysis of physical unclonable functions (PUFs). It is intended for demonstration and education purposes. See license.txt for license details. The program features a PUF visualization that demonstrates how signatures differ between PUFs and how they exhibit noise over repeated measurements. A similarity scoreboard shows the user how close the current measurement is to the closest chip signatures in the database. Other metrics such as average noise and inter-chip Hamming distances are presented to the user. Randomness tests published in NIST SP 800-22 can be computed and displayed. Noisemore » and inter-chip histograms for the sample of PUFs and repeated PUF measurements can be drawn.« less

Using Computer Graphics in Statistics.

ERIC Educational Resources Information Center

Kerley, Lyndell M.

1990-01-01

Described is software which allows a student to use simulation to produce analytical output as well as graphical results. The results include a frequency histogram of a selected population distribution, a frequency histogram of the distribution of the sample means, and test the normality distributions of the sample means. (KR)

Analyzing and Visualizing Cosmological Simulations with ParaView

NASA Astrophysics Data System (ADS)

Woodring, Jonathan; Heitmann, Katrin; Ahrens, James; Fasel, Patricia; Hsu, Chung-Hsing; Habib, Salman; Pope, Adrian

2011-07-01

The advent of large cosmological sky surveys—ushering in the era of precision cosmology—has been accompanied by ever larger cosmological simulations. The analysis of these simulations, which currently encompass tens of billions of particles and up to a trillion particles in the near future, is often as daunting as carrying out the simulations in the first place. Therefore, the development of very efficient analysis tools combining qualitative and quantitative capabilities is a matter of some urgency. In this paper, we introduce new analysis features implemented within ParaView, a fully parallel, open-source visualization toolkit, to analyze large N-body simulations. A major aspect of ParaView is that it can live and operate on the same machines and utilize the same parallel power as the simulation codes themselves. In addition, data movement is in a serious bottleneck now and will become even more of an issue in the future; an interactive visualization and analysis tool that can handle data in situ is fast becoming essential. The new features in ParaView include particle readers and a very efficient halo finder that identifies friends-of-friends halos and determines common halo properties, including spherical overdensity properties. In combination with many other functionalities already existing within ParaView, such as histogram routines or interfaces to programming languages like Python, this enhanced version enables fast, interactive, and convenient analyses of large cosmological simulations. In addition, development paths are available for future extensions.

A method of determining the presence of blood in and on a dental needle after the administration of local anesthetic.

PubMed

Kotze, Marthinus J; Labuschagne, Willemien

2014-06-01

In the study reported in this article, the authors aimed to demonstrate the presence of blood on the surface and in the lumen of two gauges of dental needles after administration of local anesthetic (LA) by using three LA-administering techniques normally used for the extraction of teeth. The authors obtained standardized photographs of 200 urine dipsticks after moistening the dipstick's chemical pads for blood with the first drop of liquid discharged from the needle lumen after LA administration. Using the histogram function of a software program, the authors analyzed differences in gray-scale values of the different blood parameters for the presence of blood. They used luminol spray to expose small quantities of blood on the surface of the needle after LA administration. Blood was identified at 39 percent in the lumen and at 16 percent on the surface of the needles when analyzed after LA administration. With the method used, it was possible to demonstrate and quantify the percentage of blood present in the lumen of needles (39 percent) after the administration of dental LA. Furthermore, the technique was adequately sensitive for demonstrating the quantity of blood in two needles of different diameters. By demonstrating the presence, as well as quantifying the percentage, of blood on two dental needles of different gauges after the administration of LA, dental health care workers can be motivated to report needlestick injuries and to follow the approved protocols recommended by their institutions.

Efficient visibility-driven medical image visualisation via adaptive binned visibility histogram.

PubMed

Jung, Younhyun; Kim, Jinman; Kumar, Ashnil; Feng, David Dagan; Fulham, Michael

2016-07-01

'Visibility' is a fundamental optical property that represents the observable, by users, proportion of the voxels in a volume during interactive volume rendering. The manipulation of this 'visibility' improves the volume rendering processes; for instance by ensuring the visibility of regions of interest (ROIs) or by guiding the identification of an optimal rendering view-point. The construction of visibility histograms (VHs), which represent the distribution of all the visibility of all voxels in the rendered volume, enables users to explore the volume with real-time feedback about occlusion patterns among spatially related structures during volume rendering manipulations. Volume rendered medical images have been a primary beneficiary of VH given the need to ensure that specific ROIs are visible relative to the surrounding structures, e.g. the visualisation of tumours that may otherwise be occluded by neighbouring structures. VH construction and its subsequent manipulations, however, are computationally expensive due to the histogram binning of the visibilities. This limits the real-time application of VH to medical images that have large intensity ranges and volume dimensions and require a large number of histogram bins. In this study, we introduce an efficient adaptive binned visibility histogram (AB-VH) in which a smaller number of histogram bins are used to represent the visibility distribution of the full VH. We adaptively bin medical images by using a cluster analysis algorithm that groups the voxels according to their intensity similarities into a smaller subset of bins while preserving the distribution of the intensity range of the original images. We increase efficiency by exploiting the parallel computation and multiple render targets (MRT) extension of the modern graphical processing units (GPUs) and this enables efficient computation of the histogram. We show the application of our method to single-modality computed tomography (CT), magnetic resonance (MR) imaging and multi-modality positron emission tomography-CT (PET-CT). In our experiments, the AB-VH markedly improved the computational efficiency for the VH construction and thus improved the subsequent VH-driven volume manipulations. This efficiency was achieved without major degradation in the VH visually and numerical differences between the AB-VH and its full-bin counterpart. We applied several variants of the K-means clustering algorithm with varying Ks (the number of clusters) and found that higher values of K resulted in better performance at a lower computational gain. The AB-VH also had an improved performance when compared to the conventional method of down-sampling of the histogram bins (equal binning) for volume rendering visualisation. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Dehmel, J.C.; Loomis, D.; Mauro, J.

Under contract to the US Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, the firms of S. Cohen & Associates, Inc. (SC&A) and Eastern Research Group (ERG) have compiled a report that describes the physical, chemical, and radiological properties of Class-A low-level radioactive waste. The report also presents information characterizing various methods and facilities used to treat and dispose non-radioactive waste. A database management program was developed for use in accessing, sorting, analyzing, and displaying the electronic data provided by EG&G. The program was used to present and aggregate data characterizing the radiological, physical, and chemical properties of the wastemore » from descriptions contained in shipping manifests. The data thus retrieved are summarized in tables, histograms, and cumulative distribution curves presenting radionuclide concentration distributions in Class-A waste as a function of waste streams, by category of waste generators, and regions of the United States. The report also provides information characterizing methods and facilities used to treat and dispose non-radioactive waste, including industrial, municipal, and hazardous waste regulated under Subparts C and D of the Resource Conservation and Recovery Act (RCRA). The information includes a list of disposal options, the geographical locations of the processing and disposal facilities, and a description of the characteristics of such processing and disposal facilities. Volume 1 contains the Executive Summary, Volume 2 presents the Class-A waste database, Volume 3 presents the information characterizing non-radioactive waste management practices and facilities, and Volumes 4 through 7 contain Appendices A through P with supporting information.« less

Gaze Fluctuations Are Not Additively Decomposable: Reply to Bogartz and Staub

ERIC Educational Resources Information Center

Kelty-Stephen, Damian G.; Mirman, Daniel

2013-01-01

Our previous work interpreted single-lognormal fits to inter-gaze distance (i.e., "gaze steps") histograms as evidence of multiplicativity and hence interactions across scales in visual cognition. Bogartz and Staub (2012) proposed that gaze steps are additively decomposable into fixations and saccades, matching the histograms better and…

Constrained VPH+: a local path planning algorithm for a bio-inspired crawling robot with customized ultrasonic scanning sensor.

PubMed

Rao, Akshay; Elara, Mohan Rajesh; Elangovan, Karthikeyan

This paper aims to develop a local path planning algorithm for a bio-inspired, reconfigurable crawling robot. A detailed description of the robotic platform is first provided, and the suitability for deployment of each of the current state-of-the-art local path planners is analyzed after an extensive literature review. The Enhanced Vector Polar Histogram algorithm is described and reformulated to better fit the requirements of the platform. The algorithm is deployed on the robotic platform in crawling configuration and favorably compared with other state-of-the-art local path planning algorithms.

92 Years of the Ising Model: A High Resolution Monte Carlo Study

NASA Astrophysics Data System (ADS)

Xu, Jiahao; Ferrenberg, Alan M.; Landau, David P.

2018-04-01

Using extensive Monte Carlo simulations that employ the Wolff cluster flipping and data analysis with histogram reweighting and quadruple precision arithmetic, we have investigated the critical behavior of the simple cubic Ising model with lattice sizes ranging from 163 to 10243. By analyzing data with cross correlations between various thermodynamic quantities obtained from the same data pool, we obtained the critical inverse temperature K c = 0.221 654 626(5) and the critical exponent of the correlation length ν = 0.629 912(86) with precision that improves upon previous Monte Carlo estimates.

Analysis of DSN software anomalies

NASA Technical Reports Server (NTRS)

Galorath, D. D.; Hecht, H.; Hecht, M.; Reifer, D. J.

1981-01-01

A categorized data base of software errors which were discovered during the various stages of development and operational use of the Deep Space Network DSN/Mark 3 System was developed. A study team identified several existing error classification schemes (taxonomies), prepared a detailed annotated bibliography of the error taxonomy literature, and produced a new classification scheme which was tuned to the DSN anomaly reporting system and encapsulated the work of others. Based upon the DSN/RCI error taxonomy, error data on approximately 1000 reported DSN/Mark 3 anomalies were analyzed, interpreted and classified. Next, error data are summarized and histograms were produced highlighting key tendencies.

Reward and uncertainty in exploration programs

NASA Technical Reports Server (NTRS)

Kaufman, G. M.; Bradley, P. G.

1971-01-01

A set of variables which are crucial to the economic outcome of petroleum exploration are discussed. These are treated as random variables; the values they assume indicate the number of successes that occur in a drilling program and determine, for a particular discovery, the unit production cost and net economic return if that reservoir is developed. In specifying the joint probability law for those variables, extreme and probably unrealistic assumptions are made. In particular, the different random variables are assumed to be independently distributed. Using postulated probability functions and specified parameters, values are generated for selected random variables, such as reservoir size. From this set of values the economic magnitudes of interest, net return and unit production cost are computed. This constitutes a single trial, and the procedure is repeated many times. The resulting histograms approximate the probability density functions of the variables which describe the economic outcomes of an exploratory drilling program.

Timeline Resource Analysis Program (TRAP): User's manual and program document

NASA Technical Reports Server (NTRS)

Sessler, J. G.

1981-01-01

The Timeline Resource Analysis Program (TRAP), developed for scheduling and timelining problems, is described. Given an activity network, TRAP generates timeline plots, resource histograms, and tabular summaries of the network, schedules, and resource levels. It is written in ANSI FORTRAN for the Honeywell SIGMA 5 computer and operates in the interactive mode using the TEKTRONIX 4014-1 graphics terminal. The input network file may be a standard SIGMA 5 file or one generated using the Interactive Graphics Design System. The timeline plots can be displayed in two orderings: according to the sequence in which the tasks were read on input, and a waterfall sequence in which the tasks are ordered by start time. The input order is especially meaningful when the network consists of several interacting subnetworks. The waterfall sequence is helpful in assessing the project status at any point in time.

Easy handling of tectonic data: the programs TectonicVB for Mac and TectonicsFP for Windows™

NASA Astrophysics Data System (ADS)

Ortner, Hugo; Reiter, Franz; Acs, Peter

2002-12-01

TectonicVB for Macintosh and TectonicsFP for Windows TM operating systems are two menu-driven computer programs which allow the shared use of data on these environments. The programs can produce stereographic plots of orientation data (great circles, poles, lineations). Frequently used statistical procedures like calculation of eigenvalues and eigenvectors, calculation of mean vector with concentration parameters and confidence cone can be easily performed. Fault data can be plotted in stereographic projection (Angelier and Hoeppener plots). Sorting of datasets into homogeneous subsets and rotation of tectonic data can be performed in interactive two-diagram windows. The paleostress tensor can be calculated from fault data sets using graphical (calculation of kinematic axes and right dihedra method) or mathematical methods (direct inversion or numerical dynamical analysis). The calculations can be checked in dimensionless Mohr diagrams and fluctuation histograms.

MRI intensity nonuniformity correction using simultaneously spatial and gray-level histogram information.

PubMed

Milles, Julien; Zhu, Yue Min; Gimenez, Gérard; Guttmann, Charles R G; Magnin, Isabelle E

2007-03-01

A novel approach for correcting intensity nonuniformity in magnetic resonance imaging (MRI) is presented. This approach is based on the simultaneous use of spatial and gray-level histogram information. Spatial information about intensity nonuniformity is obtained using cubic B-spline smoothing. Gray-level histogram information of the image corrupted by intensity nonuniformity is exploited from a frequential point of view. The proposed correction method is illustrated using both physical phantom and human brain images. The results are consistent with theoretical prediction, and demonstrate a new way of dealing with intensity nonuniformity problems. They are all the more significant as the ground truth on intensity nonuniformity is unknown in clinical images.

An effective image classification method with the fusion of invariant feature and a new color descriptor

NASA Astrophysics Data System (ADS)

Mansourian, Leila; Taufik Abdullah, Muhamad; Nurliyana Abdullah, Lili; Azman, Azreen; Mustaffa, Mas Rina

2017-02-01

Pyramid Histogram of Words (PHOW), combined Bag of Visual Words (BoVW) with the spatial pyramid matching (SPM) in order to add location information to extracted features. However, different PHOW extracted from various color spaces, and they did not extract color information individually, that means they discard color information, which is an important characteristic of any image that is motivated by human vision. This article, concatenated PHOW Multi-Scale Dense Scale Invariant Feature Transform (MSDSIFT) histogram and a proposed Color histogram to improve the performance of existing image classification algorithms. Performance evaluation on several datasets proves that the new approach outperforms other existing, state-of-the-art methods.

Post-Modeling Histogram Matching of Maps Produced Using Regression Trees

Treesearch

Andrew J. Lister; Tonya W. Lister

2006-01-01

Spatial predictive models often use statistical techniques that in some way rely on averaging of values. Estimates from linear modeling are known to be susceptible to truncation of variance when the independent (predictor) variables are measured with error. A straightforward post-processing technique (histogram matching) for attempting to mitigate this effect is...

Histogram-based automatic thresholding for bruise detection of apples by structured-illumination reflectance imaging

USDA-ARS?s Scientific Manuscript database

Thresholding is an important step in the segmentation of image features, and the existing methods are not all effective when the image histogram exhibits a unimodal pattern, which is common in defect detection of fruit. This study was aimed at developing a general automatic thresholding methodology ...

Distribution of a suite of elements including arsenic and mercury in Alabama coal

USGS Publications Warehouse

Goldhaber, Martin B.; Bigelow, R.C.; Hatch, J.R.; Pashin, J.C.

2000-01-01

Arsenic and other elements are unusually abundant in Alabama coal. This conclusion is based on chemical analyses of coal in the U.S. Geological Survey's National Coal Resources Data System (NCRDS; Bragg and others, 1994). According to NCRDS data, the average concentration of arsenic in Alabama coal (72 ppm) is three times higher than is the average for all U.S. coal (24 ppm). Of the U.S. coal analyses for arsenic that are at least 3 standard deviations above the mean, approximately 90% are from the coal fields of Alabama. Figure 1 contrasts the abundance of arsenic in coal of the Warrior field of Alabama (histogram C) with that of coal of the Powder River Basin, Wyoming (histogram A), and the Eastern Interior Province including the Illinois Basin and nearby areas (histogram B). The Warrior field is by far the largest in Alabama. On the histogram, the large 'tail' of very high values (> 200 ppm) in the Warrior coal contrasts with the other two regions that have very few analyses greater than 200 ppm.

Real-Time Tracking by Double Templates Matching Based on Timed Motion History Image with HSV Feature

PubMed Central

Li, Zhiyong; Li, Pengfei; Yu, Xiaoping; Hashem, Mervat

2014-01-01

It is a challenge to represent the target appearance model for moving object tracking under complex environment. This study presents a novel method with appearance model described by double templates based on timed motion history image with HSV color histogram feature (tMHI-HSV). The main components include offline template and online template initialization, tMHI-HSV-based candidate patches feature histograms calculation, double templates matching (DTM) for object location, and templates updating. Firstly, we initialize the target object region and calculate its HSV color histogram feature as offline template and online template. Secondly, the tMHI-HSV is used to segment the motion region and calculate these candidate object patches' color histograms to represent their appearance models. Finally, we utilize the DTM method to trace the target and update the offline template and online template real-timely. The experimental results show that the proposed method can efficiently handle the scale variation and pose change of the rigid and nonrigid objects, even in illumination change and occlusion visual environment. PMID:24592185

Adjustments for the display of quantized ion channel dwell times in histograms with logarithmic bins.

PubMed

Stark, J A; Hladky, S B

2000-02-01

Dwell-time histograms are often plotted as part of patch-clamp investigations of ion channel currents. The advantages of plotting these histograms with a logarithmic time axis were demonstrated by, J. Physiol. (Lond.). 378:141-174), Pflügers Arch. 410:530-553), and, Biophys. J. 52:1047-1054). Sigworth and Sine argued that the interpretation of such histograms is simplified if the counts are presented in a manner similar to that of a probability density function. However, when ion channel records are recorded as a discrete time series, the dwell times are quantized. As a result, the mapping of dwell times to logarithmically spaced bins is highly irregular; bins may be empty, and significant irregularities may extend beyond the duration of 100 samples. Using simple approximations based on the nature of the binning process and the transformation rules for probability density functions, we develop adjustments for the display of the counts to compensate for this effect. Tests with simulated data suggest that this procedure provides a faithful representation of the data.

Characterization of testicular germ cell tumors: Whole-lesion histogram analysis of the apparent diffusion coefficient at 3T.

PubMed

Min, Xiangde; Feng, Zhaoyan; Wang, Liang; Cai, Jie; Yan, Xu; Li, Basen; Ke, Zan; Zhang, Peipei; You, Huijuan

2018-01-01

To assess the values of parameters derived from whole-lesion histograms of the apparent diffusion coefficient (ADC) at 3T for the characterization of testicular germ cell tumors (TGCTs). A total of 24 men with TGCTs underwent 3T diffusion-weighted imaging. Fourteen tumors were pathologically confirmed as seminomas, and ten tumors were pathologically confirmed as nonseminomas. Whole-lesion histogram analysis of the ADC values was performed. A Mann-Whitney U test was employed to compare the differences in ADC histogram parameters between seminomas and nonseminomas. Receiver operating characteristic analysis was used to identify the cutoff values for each parameter for differentiating seminomas from nonseminomas; furthermore, the area under the curve (AUC) was calculated to evaluate the diagnostic accuracy. The median of 10th, 25th, 50th, 75th, and 90th percentiles and mean, minimum and maximum ADC values were all significantly reduced for seminomas compared with nonseminomas (p<0.05 for all). In contrast, the median of kurtosis and skewness of ADC values of seminomas were both significantly increased compared with those of nonseminomas (p=0.003 and 0.001, respectively). For differentiating nonseminomas from seminomas, the 10th percentile ADC yielded the highest AUC with a sensitivity and specificity of 100% and 92.86%, respectively. Whole-lesion histogram analysis of ADCs might be used for preoperative characterization of TGCTs. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantification and classification of neuronal responses in kernel-smoothed peristimulus time histograms

PubMed Central

Fried, Itzhak; Koch, Christof

2014-01-01

Peristimulus time histograms are a widespread form of visualizing neuronal responses. Kernel convolution methods transform these histograms into a smooth, continuous probability density function. This provides an improved estimate of a neuron's actual response envelope. We here develop a classifier, called the h-coefficient, to determine whether time-locked fluctuations in the firing rate of a neuron should be classified as a response or as random noise. Unlike previous approaches, the h-coefficient takes advantage of the more precise response envelope estimation provided by the kernel convolution method. The h-coefficient quantizes the smoothed response envelope and calculates the probability of a response of a given shape to occur by chance. We tested the efficacy of the h-coefficient in a large data set of Monte Carlo simulated smoothed peristimulus time histograms with varying response amplitudes, response durations, trial numbers, and baseline firing rates. Across all these conditions, the h-coefficient significantly outperformed more classical classifiers, with a mean false alarm rate of 0.004 and a mean hit rate of 0.494. We also tested the h-coefficient's performance in a set of neuronal responses recorded in humans. The algorithm behind the h-coefficient provides various opportunities for further adaptation and the flexibility to target specific parameters in a given data set. Our findings confirm that the h-coefficient can provide a conservative and powerful tool for the analysis of peristimulus time histograms with great potential for future development. PMID:25475352

Using color histogram normalization for recovering chromatic illumination-changed images.

PubMed

Pei, S C; Tseng, C L; Wu, C C

2001-11-01

We propose a novel image-recovery method using the covariance matrix of the red-green-blue (R-G-B) color histogram and tensor theories. The image-recovery method is called the color histogram normalization algorithm. It is known that the color histograms of an image taken under varied illuminations are related by a general affine transformation of the R-G-B coordinates when the illumination is changed. We propose a simplified affine model for application with illumination variation. This simplified affine model considers the effects of only three basic forms of distortion: translation, scaling, and rotation. According to this principle, we can estimate the affine transformation matrix necessary to recover images whose color distributions are varied as a result of illumination changes. We compare the normalized color histogram of the standard image with that of the tested image. By performing some operations of simple linear algebra, we can estimate the matrix of the affine transformation between two images under different illuminations. To demonstrate the performance of the proposed algorithm, we divide the experiments into two parts: computer-simulated images and real images corresponding to illumination changes. Simulation results show that the proposed algorithm is effective for both types of images. We also explain the noise-sensitive skew-rotation estimation that exists in the general affine model and demonstrate that the proposed simplified affine model without the use of skew rotation is better than the general affine model for such applications.

The impact of slice-reduced computed tomography on histogram-based densitometry assessment of lung fibrosis in patients with systemic sclerosis.

PubMed

Nguyen-Kim, Thi Dan Linh; Maurer, Britta; Suliman, Yossra A; Morsbach, Fabian; Distler, Oliver; Frauenfelder, Thomas

2018-04-01

To evaluate usability of slice-reduced sequential computed tomography (CT) compared to standard high-resolution CT (HRCT) in patients with systemic sclerosis (SSc) for qualitative and quantitative assessment of interstitial lung disease (ILD) with respect to (I) detection of lung parenchymal abnormalities, (II) qualitative and semiquantitative visual assessment, (III) quantification of ILD by histograms and (IV) accuracy for the 20%-cut off discrimination. From standard chest HRCT of 60 SSc patients sequential 9-slice-computed tomography (reduced HRCT) was retrospectively reconstructed. ILD was assessed by visual scoring and quantitative histogram parameters. Results from standard and reduced HRCT were compared using non-parametric tests and analysed by univariate linear regression analyses. With respect to the detection of parenchymal abnormalities, only the detection of intrapulmonary bronchiectasis was significantly lower in reduced HRCT compared to standard HRCT (P=0.039). No differences were found comparing visual scores for fibrosis severity and extension from standard and reduced HRCT (P=0.051-0.073). All scores correlated significantly (P<0.001) to histogram parameters derived from both, standard and reduced HRCT. Significant higher values of kurtosis and skewness for reduced HRCT were found (both P<0.001). In contrast to standard HRCT histogram parameters from reduced HRCT showed significant discrimination at cut-off 20% fibrosis (sensitivity 88% kurtosis and skewness; specificity 81% kurtosis and 86% skewness; cut-off kurtosis ≤26, cut-off skewness ≤4; both P<0.001). Reduced HRCT is a robust method to assess lung fibrosis in SSc with minimal radiation dose with no difference in scoring assessment of lung fibrosis severity and extension in comparison to standard HRCT. In contrast to standard HRCT histogram parameters derived from the approach of reduced HRCT could discriminate at a threshold of 20% lung fibrosis with high sensitivity and specificity. Hence it might be used to detect early disease progression of lung fibrosis in context of monitoring and treatment of SSc patients.

Histogram analysis of ADC in rectal cancer: associations with different histopathological findings including expression of EGFR, Hif1-alpha, VEGF, p53, PD1, and KI 67. A preliminary study.

PubMed

Meyer, Hans Jonas; Höhn, Annekathrin; Surov, Alexey

2018-04-06

Functional imaging modalities like Diffusion-weighted imaging are increasingly used to predict tumor behavior like cellularity and vascularity in different tumors. Histogram analysis is an emergent imaging analysis, in which every voxel is used to obtain a histogram and therefore statistically information about tumors can be provided. The purpose of this study was to elucidate possible associations between ADC histogram parameters and several immunhistochemical features in rectal cancer. Overall, 11 patients with histologically proven rectal cancer were included into the study. There were 2 (18.18%) females and 9 males with a mean age of 67.1 years. KI 67-index, expression of p53, EGFR, VEGF, and Hif1-alpha were semiautomatically estimated. The tumors were divided into PD1-positive and PD1-negative lesions. ADC histogram analysis was performed as a whole lesion measurement using an in-house matlab application. Spearman's correlation analysis revealed a strong correlation between EGFR expression and ADCmax (p=0.72, P=0.02). None of the vascular parameters (VEGF, Hif1-alpha) correlated with ADC parameters. Kurtosis and skewness correlated inversely with p53 expression (p=-0.64, P=0.03 and p=-0.81, P=0.002, respectively). ADCmedian and ADCmode correlated with Ki67 (p=-0.62, P=0.04 and p=-0.65, P=0.03, respectively). PD1-positive tumors showed statistically significant lower ADCmax values in comparison to PD1-negative tumors, 1.93 ± 0.36 vs 2.32 ± 0.47×10 -3 mm 2 /s, p=0.04. Several associations were identified between histogram parameter derived from ADC maps and EGFR, KI 67 and p53 expression in rectal cancer. Furthermore, ADCmax was different between PD1 positive and PD1 negative tumors indicating an important role of ADC parameters for possible future treatment prediction.

Histogram analysis of ADC in rectal cancer: associations with different histopathological findings including expression of EGFR, Hif1-alpha, VEGF, p53, PD1, and KI 67. A preliminary study

PubMed Central

Meyer, Hans Jonas; Höhn, Annekathrin; Surov, Alexey

2018-01-01

Functional imaging modalities like Diffusion-weighted imaging are increasingly used to predict tumor behavior like cellularity and vascularity in different tumors. Histogram analysis is an emergent imaging analysis, in which every voxel is used to obtain a histogram and therefore statistically information about tumors can be provided. The purpose of this study was to elucidate possible associations between ADC histogram parameters and several immunhistochemical features in rectal cancer. Overall, 11 patients with histologically proven rectal cancer were included into the study. There were 2 (18.18%) females and 9 males with a mean age of 67.1 years. KI 67-index, expression of p53, EGFR, VEGF, and Hif1-alpha were semiautomatically estimated. The tumors were divided into PD1-positive and PD1-negative lesions. ADC histogram analysis was performed as a whole lesion measurement using an in-house matlab application. Spearman's correlation analysis revealed a strong correlation between EGFR expression and ADCmax (p=0.72, P=0.02). None of the vascular parameters (VEGF, Hif1-alpha) correlated with ADC parameters. Kurtosis and skewness correlated inversely with p53 expression (p=-0.64, P=0.03 and p=-0.81, P=0.002, respectively). ADCmedian and ADCmode correlated with Ki67 (p=-0.62, P=0.04 and p=-0.65, P=0.03, respectively). PD1-positive tumors showed statistically significant lower ADCmax values in comparison to PD1-negative tumors, 1.93 ± 0.36 vs 2.32 ± 0.47×10−3mm2/s, p=0.04. Several associations were identified between histogram parameter derived from ADC maps and EGFR, KI 67 and p53 expression in rectal cancer. Furthermore, ADCmax was different between PD1 positive and PD1 negative tumors indicating an important role of ADC parameters for possible future treatment prediction. PMID:29719621

Diagnostic accuracy of ultrasonic histogram features to evaluate radiation toxicity of the parotid glands: a clinical study of xerostomia following head-and-neck cancer radiotherapy.

PubMed

Yang, Xiaofeng; Tridandapani, Srini; Beitler, Jonathan J; Yu, David S; Chen, Zhengjia; Kim, Sungjin; Bruner, Deborah W; Curran, Walter J; Liu, Tian

2014-10-01

To investigate the diagnostic accuracy of ultrasound histogram features in the quantitative assessment of radiation-induced parotid gland injury and to identify potential imaging biomarkers for radiation-induced xerostomia (dry mouth)-the most common and debilitating side effect after head-and-neck radiotherapy (RT). Thirty-four patients, who have developed xerostomia after RT for head-and-neck cancer, were enrolled. Radiation-induced xerostomia was defined by the Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer morbidity scale. Ultrasound scans were performed on each patient's parotids bilaterally. The 34 patients were stratified into the acute-toxicity groups (16 patients, ≤ 3 months after treatment) and the late-toxicity group (18 patients, > 3 months after treatment). A separate control group of 13 healthy volunteers underwent similar ultrasound scans of their parotid glands. Six sonographic features were derived from the echo-intensity histograms to assess acute and late toxicity of the parotid glands. The quantitative assessments were compared to a radiologist's clinical evaluations. The diagnostic accuracy of these ultrasonic histogram features was evaluated with the receiver operating characteristic (ROC) curve. With an area under the ROC curve greater than 0.90, several histogram features demonstrated excellent diagnostic accuracy for evaluation of acute and late toxicity of parotid glands. Significant differences (P < .05) in all six sonographic features were demonstrated between the control, acute-toxicity, and late-toxicity groups. However, subjective radiologic evaluation cannot distinguish between acute and late toxicity of parotid glands. We demonstrated that ultrasound histogram features could be used to measure acute and late toxicity of the parotid glands after head-and-neck cancer RT, which may be developed into a low-cost imaging method for xerostomia monitoring and assessment. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Subtype differentiation of renal tumors using voxel-based histogram analysis of intravoxel incoherent motion parameters.

PubMed

Gaing, Byron; Sigmund, Eric E; Huang, William C; Babb, James S; Parikh, Nainesh S; Stoffel, David; Chandarana, Hersh

2015-03-01

The aim of this study was to determine if voxel-based histogram analysis of intravoxel incoherent motion imaging (IVIM) parameters can differentiate various subtypes of renal tumors, including benign and malignant lesions. A total of 44 patients with renal tumors who underwent surgery and had histopathology available were included in this Health Insurance Portability and Accountability Act-compliant, institutional review board-approved, single-institution prospective study. In addition to routine renal magnetic resonance imaging examination performed on a 1.5-T system, all patients were imaged with axial diffusion-weighted imaging using 8 b values (range, 0-800 s/mm). A biexponential model was fitted to the diffusion signal data using a segmented algorithm to extract the IVIM parameters perfusion fraction (fp), tissue diffusivity (Dt), and pseudodiffusivity (Dp) for each voxel. Mean and histogram measures of heterogeneity (standard deviation, skewness, and kurtosis) of IVIM parameters were correlated with pathology results of tumor subtype using unequal variance t tests to compare subtypes in terms of each measure. Correction for multiple comparisons was accomplished using the Tukey honestly significant difference procedure. A total of 44 renal tumors including 23 clear cell (ccRCC), 4 papillary (pRCC), 5 chromophobe, and 5 cystic renal cell carcinomas, as well as benign lesions, 4 oncocytomas (Onc) and 3 angiomyolipomas (AMLs), were included in our analysis. Mean IVIM parameters fp and Dt differentiated 8 of 15 pairs of renal tumors. Histogram analysis of IVIM parameters differentiated 9 of 15 subtype pairs. One subtype pair (ccRCC vs pRCC) was differentiated by mean analysis but not by histogram analysis. However, 2 other subtype pairs (AML vs Onc and ccRCC vs Onc) were differentiated by histogram distribution parameters exclusively. The standard deviation of Dt [σ(Dt)] differentiated ccRCC (0.362 ± 0.136 × 10 mm/s) from AML (0.199 ± 0.043 × 10 mm/s) (P = 0.002). Kurtosis of fp separated Onc (2.767 ± 1.299) from AML (-0.325 ± 0.279; P = 0.001), ccRCC (0.612 ± 1.139; P = 0.042), and pRCC (0.308 ± 0.730; P = 0.025). Intravoxel incoherent motion imaging parameters with inclusion of histogram measures of heterogeneity can help differentiate malignant from benign lesions as well as various subtypes of renal cancers.

Tumor segmentation of multi-echo MR T2-weighted images with morphological operators

NASA Astrophysics Data System (ADS)

Torres, W.; Martín-Landrove, M.; Paluszny, M.; Figueroa, G.; Padilla, G.

2009-02-01

In the present work an automatic brain tumor segmentation procedure based on mathematical morphology is proposed. The approach considers sequences of eight multi-echo MR T2-weighted images. The relaxation time T2 characterizes the relaxation of water protons in the brain tissue: white matter, gray matter, cerebrospinal fluid (CSF) or pathological tissue. Image data is initially regularized by the application of a log-convex filter in order to adjust its geometrical properties to those of noiseless data, which exhibits monotonously decreasing convex behavior. Finally the regularized data is analyzed by means of an 8-dimensional morphological eccentricity filter. In a first stage, the filter was used for the spatial homogenization of the tissues in the image, replacing each pixel by the most representative pixel within its structuring element, i.e. the one which exhibits the minimum total distance to all members in the structuring element. On the filtered images, the relaxation time T2 is estimated by means of least square regression algorithm and the histogram of T2 is determined. The T2 histogram was partitioned using the watershed morphological operator; relaxation time classes were established and used for tissue classification and segmentation of the image. The method was validated on 15 sets of MRI data with excellent results.

Volume adjustment of lung density by computed tomography scans in patients with emphysema.

PubMed

Shaker, S B; Dirksen, A; Laursen, L C; Skovgaard, L T; Holstein-Rathlou, N H

2004-07-01

To determine how to adjust lung density measurements for the volume of the lung calculated from computed tomography (CT) scans in patients with emphysema. Fifty patients with emphysema underwent 3 CT scans at 2-week intervals. The scans were analyzed with a software package that detected the lung in contiguous images and subsequently generated a histogram of the pixel attenuation values. The total lung volume (TLV), lung weight, percentile density (PD), and relative area of emphysema (RA) were calculated from this histogram. RA and PD are commonly applied measures of pulmonary emphysema derived from CT scans. These parameters are markedly influenced by changes in the level of inspiration. The variability of lung density due to within-subject variation in TLV was explored by plotting TLV against PD and RA. The coefficients for volume adjustment for PD were relatively stable over a wide range from the 10th to the 80th percentile, whereas for RA the coefficients showed large variability especially in the lower range, which is the most relevant for quantitation of pulmonary emphysema. Volume adjustment is mandatory in repeated CT densitometry and is more robust for PD than for RA. Therefore, PD seems more suitable for monitoring the progression of emphysema.

Sonoelastography of Plantar Fascia: Reproducibility and Pattern Description in Healthy Subjects and Symptomatic Subjects.

PubMed

Ríos-Díaz, José; Martínez-Payá, Jacinto J; del Baño-Aledo, María Elena; de Groot-Ferrando, Ana; Botía-Castillo, Paloma; Fernández-Rodríguez, David

2015-10-01

The purpose of the work reported here was to describe the sonoelastographic appearance of the plantar fascia of healthy volunteers and patients with fasciitis. Twenty-three healthy subjects and 21 patients with plantar fasciitis were examined using B-mode and real-time sonoelastography (RTSR) scanning. B-Mode examination included fascia thickness and echotexture. Echogenicity and echovariation of the color histogram were analyzed. Fasciae were classified into type 1, blue (more elastic); type 2, blue/green (intermediate); or type 3, green (less elastic). RTSE revealed 72.7% of fasciae as type 2, with no significant association with fasciitis (χ(2) = 3.6, df = 2, p = 0.17). Quantitative analysis of the color histogram revealed a significantly greater intensity of green (mean = 77.8, 95% confidence interval [CI] = 71.9-83.6) and blue (mean = 74.2, 95% CI = 69.7-78.8) in healthy subjects. Echovariation of the color red was 33.4% higher in the fasciitis group than in the healthy group (95% CI = 16.7-50.1). Sonoelastography with quantitative analysis of echovariation can be a useful tool for evaluation of plantar fascia pathology. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Comparison of optimization algorithms in intensity-modulated radiation therapy planning

NASA Astrophysics Data System (ADS)

Kendrick, Rachel

Intensity-modulated radiation therapy is used to better conform the radiation dose to the target, which includes avoiding healthy tissue. Planning programs employ optimization methods to search for the best fluence of each photon beam, and therefore to create the best treatment plan. The Computational Environment for Radiotherapy Research (CERR), a program written in MATLAB, was used to examine some commonly-used algorithms for one 5-beam plan. Algorithms include the genetic algorithm, quadratic programming, pattern search, constrained nonlinear optimization, simulated annealing, the optimization method used in Varian EclipseTM, and some hybrids of these. Quadratic programing, simulated annealing, and a quadratic/simulated annealing hybrid were also separately compared using different prescription doses. The results of each dose-volume histogram as well as the visual dose color wash were used to compare the plans. CERR's built-in quadratic programming provided the best overall plan, but avoidance of the organ-at-risk was rivaled by other programs. Hybrids of quadratic programming with some of these algorithms seems to suggest the possibility of better planning programs, as shown by the improved quadratic/simulated annealing plan when compared to the simulated annealing algorithm alone. Further experimentation will be done to improve cost functions and computational time.

Assessment of treatment response during chemoradiation therapy for pancreatic cancer based on quantitative radiomic analysis of daily CTs: An exploratory study.

PubMed

Chen, Xiaojian; Oshima, Kiyoko; Schott, Diane; Wu, Hui; Hall, William; Song, Yingqiu; Tao, Yalan; Li, Dingjie; Zheng, Cheng; Knechtges, Paul; Erickson, Beth; Li, X Allen

2017-01-01

In an effort for early assessment of treatment response, we investigate radiation induced changes in quantitative CT features of tumor during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Diagnostic-quality CT data acquired daily during routine CT-guided CRT using a CT-on-rails for 20 pancreatic head cancer patients were analyzed. On each daily CT, the pancreatic head, the spinal cord and the aorta were delineated and the histograms of CT number (CTN) in these contours were extracted. Eight histogram-based radiomic metrics including the mean CTN (MCTN), peak position, volume, standard deviation (SD), skewness, kurtosis, energy and entropy were calculated for each fraction. Paired t-test was used to check the significance of the change of specific metric at specific time. GEE model was used to test the association between changes of metrics over time for different pathology responses. In general, CTN histogram in the pancreatic head (but not in spinal cord) changed during the CRT delivery. Changes from the 1st to the 26th fraction in MCTN ranged from -15.8 to 3.9 HU with an average of -4.7 HU (p<0.001). Meanwhile the volume decreased, the skewness increased (less skewed), and the kurtosis decreased (less peaked). The changes of MCTN, volume, skewness, and kurtosis became significant after two weeks of treatment. Patient pathological response is associated with the changes of MCTN, SD, and skewness. In cases of good response, patients tend to have large reductions in MCTN and skewness, and large increases in SD and kurtosis. Significant changes in CT radiomic features, such as the MCTN, skewness, and kurtosis in tumor were observed during the course of CRT for pancreas cancer based on quantitative analysis of daily CTs. These changes may be potentially used for early assessment of treatment response and stratification for therapeutic intensification.

On algorithmic optimization of histogramming functions for GEM systems

NASA Astrophysics Data System (ADS)

Krawczyk, Rafał D.; Czarski, Tomasz; Kolasinski, Piotr; Poźniak, Krzysztof T.; Linczuk, Maciej; Byszuk, Adrian; Chernyshova, Maryna; Juszczyk, Bartlomiej; Kasprowicz, Grzegorz; Wojenski, Andrzej; Zabolotny, Wojciech

2015-09-01

This article concerns optimization methods for data analysis for the X-ray GEM detector system. The offline analysis of collected samples was optimized for MATLAB computations. Compiled functions in C language were used with MEX library. Significant speedup was received for both ordering-preprocessing and for histogramming of samples. Utilized techniques with obtained results are presented.

Students' Misconceptions in Interpreting Center and Variability of Data Represented via Histograms and Stem-and-Leaf Plots

ERIC Educational Resources Information Center

Cooper, Linda L.; Shore, Felice S.

2008-01-01

This paper identifies and discusses misconceptions that students have in making judgments of center and variability when data are presented graphically. An assessment addressing interpreting center and variability in histograms and stem-and-leaf plots was administered to, and follow-up interviews were conducted with, undergraduates enrolled in…

Texture and phase analysis of deformed SUS304 by using HIPPO

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

Takajo, Shigehiro; Vogel, Sven C.

2016-11-15

These slides represent the author's research activity at Los Alamos National Laboratory (LANL), which is about texture and phase analysis of deformed SUS304 by using HIPPO. The following topics are covered: diffraction histogram at each sample position, diffraction histogram (all bank data averaged), possiblity of ε-phase, MAUD analysis with including ε-phase.

Shift-Invariant Image Reconstruction of Speckle-Degraded Images Using Bispectrum Estimation

DTIC Science & Technology

1990-05-01

process with the requisite negative exponential pelf. I call this model the Negative Exponential Model ( NENI ). The NENI flowchart is seen in Figure 6...Figure ]3d-g. Statistical Histograms and Phase for the RPj NG EXP FDF MULT METHOD FILuteC 14a. Truth Object Speckled Via the NENI HISTOGRAM OF SPECKLE

The mineralogical and chronological evidences of subducted continent material in deep mantle: diamond, zircon and rutile separated from the Horoman peridotite of Japan

NASA Astrophysics Data System (ADS)

Li, Y.; Yang, J.; Nida, K.; Yamamoto, S.; Lin, Y.; Li, Q.; Tian, M.; Kon, Y.; Komiya, T.; Maruyama, S.

2017-12-01

The Horoman peridotite complex is an Alpine-type orogenic lherzolite massif of upper-mantle in the Hidaka metamorphic belt, Hokkaido, Japan. The peridotite complex is composed of dunite, harzburgite, spinel lherzolite and plagioclase lherzolite, exhibits a conspicuous layered structure, which is a product of a Cretaceous to early Paleogene arc-trench system formed by westward subduction of an oceanic plate between the paleo-Eurasian and paleo-North American Plates. Various combinations of diamond, corundum, moissanite, zircon, monazite, rutile, and kyanite have been separated from spinel harzburgite (700 kg) and lherzolite (500 kg), respectively. The carbon isotopes analyses of diamond grains by Nano-SIMS yielded significant light carbon isotopes feature as δ13 CPDB values ranging from -29.2 ‰ to -17.2 ‰, with an average of -22.8±0.32 ‰. Zircon grains occur as sub-angular to round in morphological characteristics, similar to zircons of crustal sedimentary rocks. Many zircons contain small inclusions, comprise of quartz, apatite, rutile and muscovite. The U-Pb age of zircon grains analyzed using LA-ICP-MS and SIMS gave a wide age range, from the Jurassic to Archean (ca 159 - 3131 Ma). In the zircon age histogram, four age groups were identified; the age peaks are 2385 Ma, 1890 Ma, 1618 Ma and 1212 Ma, respectively. On the other hand, U-Pb ages of rutile grains analyzed using SIMS gave a peak of 370 Ma in age histogram. The mineralogical and chronological evidences of numerous crustal minerals in peridotite of Horoman suggest that the ancient continent material was subducted in deep mantle and recycled through the upper mantle by multicycle subduction processes.

Encoding of a spectrally-complex communication sound in the bullfrog's auditory nerve.

PubMed

Schwartz, J J; Simmons, A M

1990-02-01

1. A population study of eighth nerve responses in the bullfrog, Rana catesbeiana, was undertaken to analyze how the eighth nerve codes the complex spectral and temporal structure of the species-specific advertisement call over a biologically-realistic range of intensities. Synthetic advertisement calls were generated by Fourier synthesis and presented to individual eighth nerve fibers of anesthetized bullfrogs. Fiber responses were analyzed by calculating rate responses based on post-stimulus-time (PST) histograms and temporal responses based on Fourier transforms of period histograms. 2. At stimulus intensities of 70 and 80 dB SPL, normalized rate responses provide a fairly good representation of the complex spectral structure of the stimulus, particularly in the low- and mid-frequency range. At higher intensities, rate responses saturate, and very little of the spectral structure of the complex stimulus can be seen in the profile of rate responses of the population. 3. Both AP and BP fibers phase-lock strongly to the fundamental (100 Hz) of the complex stimulus. These effects are relatively resistant to changes in stimulus intensity. Only a small number of fibers synchronize to the low-frequency spectral energy in the stimulus. The underlying spectral complexity of the stimulus is not accurately reflected in the timing of fiber firing, presumably because firing is 'captured' by the fundamental frequency. 4. Plots of average localized synchronized rate (ALSR), which combine both spectral and temporal information, show a similar, low-pass shape at all stimulus intensities. ALSR plots do not generally provide an accurate representation of the structure of the advertisement call. 5. The data suggest that anuran peripheral auditory fibers may be particularly sensitive to the amplitude envelope of sounds.

Damage Proxy Map from Interferometric Synthetic Aperture Radar Coherence

NASA Technical Reports Server (NTRS)

Webb, Frank H. (Inventor); Yun, Sang-Ho (Inventor); Fielding, Eric Jameson (Inventor); Simons, Mark (Inventor)

2015-01-01

A method, apparatus, and article of manufacture provide the ability to generate a damage proxy map. A master coherence map and a slave coherence map, for an area prior and subsequent to (including) a damage event are obtained. The slave coherence map is registered to the master coherence map. Pixel values of the slave coherence map are modified using histogram matching to provide a first histogram of the master coherence map that exactly matches a second histogram of the slave coherence map. A coherence difference between the slave coherence map and the master coherence map is computed to produce a damage proxy map. The damage proxy map is displayed with the coherence difference displayed in a visually distinguishable manner.

NURE aerial gamma ray and magnetic detail survey of portions of northeast Washington. Final report

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

Not Available

1981-11-01

The Northeast Washington Survey was performed under the United States Department of Energy's National Uranium Resource Evaluation (NURE) Program, which is designed to provide radioelement distribution information to assist in assessing the uraniferous material potential of the United States. The radiometric and ancilliary data were digitally recorded and processed. The results are presented in the form of stacked profiles, contour maps, flight path maps, statistical tables and frequency distribution histograms. These graphical outputs are presented at a scale of 1:62,500 and are contained in the individual Volume 2 reports.

Soot Nanostructure: Using Fringe Analysis Software on High Resolution Transmission Electron Microscopy of Carbon Soot

NASA Technical Reports Server (NTRS)

King, James D.

2004-01-01

Using high resolution transmission electron images of carbon nanotubes and carbon particles, we are able to use image analysis program to determine several carbon fringe properties, including length, separation, curvature and orientation. Results are shown in the form of histograms for each of those quantities. The combination of those measurements can give a better indication of the graphic structure within nanotubes and particles of carbon and can distinguish carbons based upon fringe properties. Carbon with longer, straighter and closer spaced fringes are considered graphite, while amorphous carbon contain shorter, less structured fringes.

SU-E-T-275: Radiobiological Evaluation of Intensity Modulated Radiotherapy Treatment for Locally Advanced Head and Neck Squamous Cell Carcinomas

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

Rekha Reddy, B.; Ravikumar, M.; Tanvir Pasha, C.R

2014-06-01

Purpose: To evaluate the radiobiological outcome of Intensity Modulated Radiotherapy Treatment (IMRT) for locally advanced head and neck squamous cell carcinomas using HART (Histogram Analysis in Radiation Therapy; J Appl Clin Med Phys 11(1): 137–157, 2010) program and compare with the clinical outcomes. Methods: We have treated 20 patients of stage III and IV HNSCC Oropharynx and hypopharynx with accelerated IMRT technique and concurrent chemotherapy. Delineation of tumor and normal tissues were done using Danish Head and Neck Cancer Group (DAHANCA) contouring guidelines and radiotherapy was delivered to a dose of 70Gy in 35 fractions to the primary and involvedmore » lymph nodes, 63Gy to intermediate risk areas and 56 Gy to lower risk areas, Monday to Saturday, 6 Days/week using 6 MV Photons with an expected overall treatment time of 6 weeks. The TCP and NTCP's were calculated from the dose-volume histogram (DVH) statistics using the Poisson Statistics (PS) and JT Lyman models respectively and the Resultwas correlated with clinical outcomes of the patients with mean follow up of 24 months. Results: Using HART program, the TCP (0.89± 0.01) of primary tumor and the NTCP for parotids (0.20±0.12), spinal cord (0.05±0.01), esophagus (0.30±0.2), mandible (0.35±0.21), Oral cavity (0.37±0.18), Larynx (0.30±0.15) were estimated and correlated with clinical outcome of the patients. Conclusion: Accelerated IMRT with Chemotherapy is a clinical feasible option in the treatment of locally advanced HNSCC with encouraging initial tumour response and acceptable acute toxicities. The correlation between the clinical outcomes and radiobiological model estimated parameters using HART programs are found to be satisfactory.« less

NURE aerial gamma-ray and magnetic-reconnaissance survey portions of New Mexico, Arizona, and Texas. Volume I. Instrumentation and data reduction. Final report

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

Not Available

As part of the Department of Energy (DOE) National Uranium Resource Evaluation Program, a rotary-wing high sensitivity radiometric and magnetic survey was flown covering portions of the State of New Mexico, Arizona and Texas. The survey encompassed six 1:250,000 scale quadrangles, Holbrook, El Paso, Las Cruces, Carlsbad, Fort Sumner and Roswell. The survey was flown with a Sikorsky S58T helicopter equipped with a high sensitivity gamma ray spectrometer which was calibrated at the DOE calibration facilities at Walker Field in Grand Junction, Colorado, and the Dynamic Test Range at Lake Mead, Arizona. The radiometric data were processed to compensate formore » Compton scattering effects and altitude variations. The data were normalized to 400 feet terrain clearance. The reduced data is presented in the form of stacked profiles, standard deviation anomaly plots, histogram plots and microfiche listings. The results of the geologic interpretation of the radiometric data together with the profiles, anomaly maps and histograms are presented in the individual quadrangle reports. The survey was awarded to LKB Resources, Inc. which completed the data acquisition. In April, 1980 Carson Helicopters, Inc. and Carson Geoscience Company agreed to manage the project and complete delivery of this final report.« less

Nanomechanical characterization of heterogeneous and hierarchical biomaterials and tissues using nanoindentation: the role of finite mixture models.

PubMed

Zadpoor, Amir A

2015-03-01

Mechanical characterization of biological tissues and biomaterials at the nano-scale is often performed using nanoindentation experiments. The different constituents of the characterized materials will then appear in the histogram that shows the probability of measuring a certain range of mechanical properties. An objective technique is needed to separate the probability distributions that are mixed together in such a histogram. In this paper, finite mixture models (FMMs) are proposed as a tool capable of performing such types of analysis. Finite Gaussian mixture models assume that the measured probability distribution is a weighted combination of a finite number of Gaussian distributions with separate mean and standard deviation values. Dedicated optimization algorithms are available for fitting such a weighted mixture model to experimental data. Moreover, certain objective criteria are available to determine the optimum number of Gaussian distributions. In this paper, FMMs are used for interpreting the probability distribution functions representing the distributions of the elastic moduli of osteoarthritic human cartilage and co-polymeric microspheres. As for cartilage experiments, FMMs indicate that at least three mixture components are needed for describing the measured histogram. While the mechanical properties of the softer mixture components, often assumed to be associated with Glycosaminoglycans, were found to be more or less constant regardless of whether two or three mixture components were used, those of the second mixture component (i.e. collagen network) considerably changed depending on the number of mixture components. Regarding the co-polymeric microspheres, the optimum number of mixture components estimated by the FMM theory, i.e. 3, nicely matches the number of co-polymeric components used in the structure of the polymer. The computer programs used for the presented analyses are made freely available online for other researchers to use. Copyright © 2014 Elsevier B.V. All rights reserved.

Implementation of age and gender recognition system for intelligent digital signage

NASA Astrophysics Data System (ADS)

Lee, Sang-Heon; Sohn, Myoung-Kyu; Kim, Hyunduk

2015-12-01

Intelligent digital signage systems transmit customized advertising and information by analyzing users and customers, unlike existing system that presented advertising in the form of broadcast without regard to type of customers. Currently, development of intelligent digital signage system has been pushed forward vigorously. In this study, we designed a system capable of analyzing gender and age of customers based on image obtained from camera, although there are many different methods for analyzing customers. We conducted age and gender recognition experiments using public database. The age/gender recognition experiments were performed through histogram matching method by extracting Local binary patterns (LBP) features after facial area on input image was normalized. The results of experiment showed that gender recognition rate was as high as approximately 97% on average. Age recognition was conducted based on categorization into 5 age classes. Age recognition rates for women and men were about 67% and 68%, respectively when that conducted separately for different gender.

Histogram analysis parameters identify multiple associations between DWI and DCE MRI in head and neck squamous cell carcinoma.

PubMed

Meyer, Hans Jonas; Leifels, Leonard; Schob, Stefan; Garnov, Nikita; Surov, Alexey

2018-01-01

Nowadays, multiparametric investigations of head and neck squamous cell carcinoma (HNSCC) are established. These approaches can better characterize tumor biology and behavior. Diffusion weighted imaging (DWI) can by means of apparent diffusion coefficient (ADC) quantitatively characterize different tissue compartments. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) reflects perfusion and vascularization of tissues. Recently, a novel approach of data acquisition, namely histogram analysis of different images is a novel diagnostic approach, which can provide more information of tissue heterogeneity. The purpose of this study was to analyze possible associations between DWI, and DCE parameters derived from histogram analysis in patients with HNSCC. Overall, 34 patients, 9 women and 25 men, mean age, 56.7±10.2years, with different HNSCC were involved in the study. DWI was obtained by using of an axial echo planar imaging sequence with b-values of 0 and 800s/mm 2 . Dynamic T1w DCE sequence after intravenous application of contrast medium was performed for estimation of the following perfusion parameters: volume transfer constant (K trans ), volume of the extravascular extracellular leakage space (Ve), and diffusion of contrast medium from the extravascular extracellular leakage space back to the plasma (Kep). Both ADC and perfusion parameters maps were processed offline in DICOM format with custom-made Matlab-based application. Thereafter, polygonal ROIs were manually drawn on the transferred maps on each slice. For every parameter, mean, maximal, minimal, and median values, as well percentiles 10th, 25th, 75th, 90th, kurtosis, skewness, and entropy were estimated. Сorrelation analysis identified multiple statistically significant correlations between the investigated parameters. Ve related parameters correlated well with different ADC values. Especially, percentiles 10 and 75, mode, and median values showed stronger correlations in comparison to other parameters. Thereby, the calculated correlation coefficients ranged from 0.62 to 0.69. Furthermore, K trans related parameters showed multiple slightly to moderate significant correlations with different ADC values. Strongest correlations were identified between ADC P75 and K trans min (p=0.58, P=0.0007), and ADC P75 and K trans P10 (p=0.56, P=0.001). Only four K ep related parameters correlated statistically significant with ADC fractions. Strongest correlation was found between K ep max and ADC mode (p=-0.47, P=0.008). Multiple statistically significant correlations between, DWI and DCE MRI parameters derived from histogram analysis were identified in HNSCC. Copyright © 2017 Elsevier Inc. All rights reserved.

Motor Oil Classification using Color Histograms and Pattern Recognition Techniques.

PubMed

Ahmadi, Shiva; Mani-Varnosfaderani, Ahmad; Habibi, Biuck

2018-04-20

Motor oil classification is important for quality control and the identification of oil adulteration. In thiswork, we propose a simple, rapid, inexpensive and nondestructive approach based on image analysis and pattern recognition techniques for the classification of nine different types of motor oils according to their corresponding color histograms. For this, we applied color histogram in different color spaces such as red green blue (RGB), grayscale, and hue saturation intensity (HSI) in order to extract features that can help with the classification procedure. These color histograms and their combinations were used as input for model development and then were statistically evaluated by using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and support vector machine (SVM) techniques. Here, two common solutions for solving a multiclass classification problem were applied: (1) transformation to binary classification problem using a one-against-all (OAA) approach and (2) extension from binary classifiers to a single globally optimized multilabel classification model. In the OAA strategy, LDA, QDA, and SVM reached up to 97% in terms of accuracy, sensitivity, and specificity for both the training and test sets. In extension from binary case, despite good performances by the SVM classification model, QDA and LDA provided better results up to 92% for RGB-grayscale-HSI color histograms and up to 93% for the HSI color map, respectively. In order to reduce the numbers of independent variables for modeling, a principle component analysis algorithm was used. Our results suggest that the proposed method is promising for the identification and classification of different types of motor oils.

Whole-tumor apparent diffusion coefficient (ADC) histogram analysis to differentiate benign peripheral neurogenic tumors from soft tissue sarcomas.

PubMed

Nakajo, Masanori; Fukukura, Yoshihiko; Hakamada, Hiroto; Yoneyama, Tomohide; Kamimura, Kiyohisa; Nagano, Satoshi; Nakajo, Masayuki; Yoshiura, Takashi

2018-02-22

Apparent diffusion coefficient (ADC) histogram analyses have been used to differentiate tumor grades and predict therapeutic responses in various anatomic sites with moderate success. To determine the ability of diffusion-weighted imaging (DWI) with a whole-tumor ADC histogram analysis to differentiate benign peripheral neurogenic tumors (BPNTs) from soft tissue sarcomas (STSs). Retrospective study, single institution. In all, 25 BPNTs and 31 STSs. Two-b value DWI (b-values = 0, 1000s/mm 2 ) was at 3.0T. The histogram parameters of whole-tumor for ADC were calculated by two radiologists and compared between BPNTs and STSs. Nonparametric tests were performed for comparisons between BPNTs and STSs. P < 0.05 was considered statistically significant. The ability of each parameter to differentiate STSs from BPNTs was evaluated using area under the curve (AUC) values derived from a receiver operating characteristic curve analysis. The mean ADC and all percentile parameters were significantly lower in STSs than in BPNTs (P < 0.001-0.009), with AUCs of 0.703-0.773. However, the coefficient of variation (P = 0.020 and AUC = 0.682) and skewness (P = 0.012 and AUC = 0.697) were significantly higher in STSs than in BPNTs. Kurtosis (P = 0.295) and entropy (P = 0.604) did not differ significantly between BPNTs and STSs. Whole-tumor ADC histogram parameters except kurtosis and entropy differed significantly between BPNTs and STSs. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Histogram analysis of diffusion kurtosis imaging derived maps may distinguish between low and high grade gliomas before surgery.

PubMed

Qi, Xi-Xun; Shi, Da-Fa; Ren, Si-Xie; Zhang, Su-Ya; Li, Long; Li, Qing-Chang; Guan, Li-Ming

2018-04-01

To investigate the value of histogram analysis of diffusion kurtosis imaging (DKI) maps in the evaluation of glioma grading. A total of 39 glioma patients who underwent preoperative magnetic resonance imaging (MRI) were classified into low-grade (13 cases) and high-grade (26 cases) glioma groups. Parametric DKI maps were derived, and histogram metrics between low- and high-grade gliomas were analysed. The optimum diagnostic thresholds of the parameters, area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were achieved using a receiver operating characteristic (ROC). Significant differences were observed not only in 12 metrics of histogram DKI parameters (P<0.05), but also in mean diffusivity (MD) and mean kurtosis (MK) values, including age as a covariate (F=19.127, P<0.001 and F=20.894, P<0.001, respectively), between low- and high-grade gliomas. Mean MK was the best independent predictor of differentiating glioma grades (B=18.934, 22.237 adjusted for age, P<0.05). The partial correlation coefficient between fractional anisotropy (FA) and kurtosis fractional anisotropy (KFA) was 0.675 (P<0.001). The AUC of the mean MK, sensitivity, and specificity were 0.925, 88.5% and 84.6%, respectively. DKI parameters can effectively distinguish between low- and high-grade gliomas. Mean MK is the best independent predictor of differentiating glioma grades. • DKI is a new and important method. • DKI can provide additional information on microstructural architecture. • Histogram analysis of DKI may be more effective in glioma grading.

Whole-tumour diffusion kurtosis MR imaging histogram analysis of rectal adenocarcinoma: Correlation with clinical pathologic prognostic factors.

PubMed

Cui, Yanfen; Yang, Xiaotang; Du, Xiaosong; Zhuo, Zhizheng; Xin, Lei; Cheng, Xintao

2018-04-01

To investigate potential relationships between diffusion kurtosis imaging (DKI)-derived parameters using whole-tumour volume histogram analysis and clinicopathological prognostic factors in patients with rectal adenocarcinoma. 79 consecutive patients who underwent MRI examination with rectal adenocarcinoma were retrospectively evaluated. Parameters D, K and conventional ADC were measured using whole-tumour volume histogram analysis. Student's t-test or Mann-Whitney U-test, receiver operating characteristic curves and Spearman's correlation were used for statistical analysis. Almost all the percentile metrics of K were correlated positively with nodal involvement, higher histological grades, the presence of lymphangiovascular invasion (LVI) and circumferential margin (CRM) (p<0.05), with the exception of between K 10th , K 90th and histological grades. In contrast, significant negative correlations were observed between 25th, 50th percentiles and mean values of ADC and D, as well as ADC 10th , with tumour T stages (p< 0.05). Meanwhile, lower 75th and 90th percentiles of ADC and D values were also correlated inversely with nodal involvement (p< 0.05). K mean showed a relatively higher area under the curve (AUC) and higher specificity than other percentiles for differentiation of lesions with nodal involvement. DKI metrics with whole-tumour volume histogram analysis, especially K parameters, were associated with important prognostic factors of rectal cancer. • K correlated positively with some important prognostic factors of rectal cancer. • K mean showed higher AUC and specificity for differentiation of nodal involvement. • DKI metrics with whole-tumour volume histogram analysis depicted tumour heterogeneity.

Apparent diffusion coefficient histogram metrics correlate with survival in diffuse intrinsic pontine glioma: a report from the Pediatric Brain Tumor Consortium

PubMed Central

Poussaint, Tina Young; Vajapeyam, Sridhar; Ricci, Kelsey I.; Panigrahy, Ashok; Kocak, Mehmet; Kun, Larry E.; Boyett, James M.; Pollack, Ian F.; Fouladi, Maryam

2016-01-01

Background Diffuse intrinsic pontine glioma (DIPG) is associated with poor survival regardless of therapy. We used volumetric apparent diffusion coefficient (ADC) histogram metrics to determine associations with progression-free survival (PFS) and overall survival (OS) at baseline and after radiation therapy (RT). Methods Baseline and post-RT quantitative ADC histograms were generated from fluid-attenuated inversion recovery (FLAIR) images and enhancement regions of interest. Metrics assessed included number of peaks (ie, unimodal or bimodal), mean and median ADC, standard deviation, mode, skewness, and kurtosis. Results Based on FLAIR images, the majority of tumors had unimodal peaks with significantly shorter average survival. Pre-RT FLAIR mean, mode, and median values were significantly associated with decreased risk of progression; higher pre-RT ADC values had longer PFS on average. Pre-RT FLAIR skewness and standard deviation were significantly associated with increased risk of progression; higher pre-RT FLAIR skewness and standard deviation had shorter PFS. Nonenhancing tumors at baseline showed higher ADC FLAIR mean values, lower kurtosis, and higher PFS. For enhancing tumors at baseline, bimodal enhancement histograms had much worse PFS and OS than unimodal cases and significantly lower mean peak values. Enhancement in tumors only after RT led to significantly shorter PFS and OS than in patients with baseline or no baseline enhancement. Conclusions ADC histogram metrics in DIPG demonstrate significant correlations between diffusion metrics and survival, with lower diffusion values (increased cellularity), increased skewness, and enhancement associated with shorter survival, requiring future investigations in large DIPG clinical trials. PMID:26487690

Issues around Creating a Reusable Learning Object to Support Statistics Teaching

ERIC Educational Resources Information Center

Gilchrist, Mollie

2007-01-01

Although our health professional students have some experience of simple charts, such as pie and bar, and some intuition of histograms, they do not appear to have much knowledge or understanding about box and whisker plots and their relation to the data they are describing or compared to histograms. The boxplot is a versatile charting tool, useful…

ON THE THEORY AND PROCEDURE FOR CONSTRUCTING A MINIMAL-LENGTH, AREA-CONSERVING FREQUENCY POLYGON FROM GROUPED DATA.

ERIC Educational Resources Information Center

CASE, C. MARSTON

THIS PAPER IS CONCERNED WITH GRAPHIC PRESENTATION AND ANALYSIS OF GROUPED OBSERVATIONS. IT PRESENTS A METHOD AND SUPPORTING THEORY FOR THE CONSTRUCTION OF AN AREA-CONSERVING, MINIMAL LENGTH FREQUENCY POLYGON CORRESPONDING TO A GIVEN HISTOGRAM. TRADITIONALLY, THE CONCEPT OF A FREQUENCY POLYGON CORRESPONDING TO A GIVEN HISTOGRAM HAS REFERRED TO THAT…

Methods for Determining Particle Size Distributions from Nuclear Detonations.

DTIC Science & Technology

1987-03-01

Debris . . . 30 IV. Summary of Sample Preparation Method . . . . 35 V. Set Parameters for PCS ... ........... 39 VI. Analysis by Vendors...54 XV. Results From Brookhaven Analysis Using The Method of Cumulants ... ........... . 54 XVI. Results From Brookhaven Analysis of Sample...R-3 Using Histogram Method ......... .55 XVII. Results From Brookhaven Analysis of Sample R-8 Using Histogram Method ........... 56 XVIII.TEM Particle

Diffusion profiling of tumor volumes using a histogram approach can predict proliferation and further microarchitectural features in medulloblastoma.

PubMed

Schob, Stefan; Beeskow, Anne; Dieckow, Julia; Meyer, Hans-Jonas; Krause, Matthias; Frydrychowicz, Clara; Hirsch, Franz-Wolfgang; Surov, Alexey

2018-05-31

Medulloblastomas are the most common central nervous system tumors in childhood. Treatment and prognosis strongly depend on histology and transcriptomic profiling. However, the proliferative potential also has prognostical value. Our study aimed to investigate correlations between histogram profiling of diffusion-weighted images and further microarchitectural features. Seven patients (age median 14.6 years, minimum 2 years, maximum 20 years; 5 male, 2 female) were included in this retrospective study. Using a Matlab-based analysis tool, histogram analysis of whole apparent diffusion coefficient (ADC) volumes was performed. ADC entropy revealed a strong inverse correlation with the expression of the proliferation marker Ki67 (r = - 0.962, p = 0.009) and with total nuclear area (r = - 0.888, p = 0.044). Furthermore, ADC percentiles, most of all ADCp90, showed significant correlations with Ki67 expression (r = 0.902, p = 0.036). Diffusion histogram profiling of medulloblastomas provides valuable in vivo information which potentially can be used for risk stratification and prognostication. First of all, entropy revealed to be the most promising imaging biomarker. However, further studies are warranted.

Novel Variants of a Histogram Shift-Based Reversible Watermarking Technique for Medical Images to Improve Hiding Capacity

PubMed Central

Tuckley, Kushal

2017-01-01

In telemedicine systems, critical medical data is shared on a public communication channel. This increases the risk of unauthorised access to patient's information. This underlines the importance of secrecy and authentication for the medical data. This paper presents two innovative variations of classical histogram shift methods to increase the hiding capacity. The first technique divides the image into nonoverlapping blocks and embeds the watermark individually using the histogram method. The second method separates the region of interest and embeds the watermark only in the region of noninterest. This approach preserves the medical information intact. This method finds its use in critical medical cases. The high PSNR (above 45 dB) obtained for both techniques indicates imperceptibility of the approaches. Experimental results illustrate superiority of the proposed approaches when compared with other methods based on histogram shifting techniques. These techniques improve embedding capacity by 5–15% depending on the image type, without affecting the quality of the watermarked image. Both techniques also enable lossless reconstruction of the watermark and the host medical image. A higher embedding capacity makes the proposed approaches attractive for medical image watermarking applications without compromising the quality of the image. PMID:29104744

Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT.

PubMed

Meng, Jie; Zhu, Lijing; Zhu, Li; Xie, Li; Wang, Huanhuan; Liu, Song; Yan, Jing; Liu, Baorui; Guan, Yue; He, Jian; Ge, Yun; Zhou, Zhengyang; Yang, Xiaofeng

2017-11-03

To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram and texture analysis in predicting tumor recurrence of advanced cervical cancer treated with concurrent chemo-radiotherapy (CCRT). 36 women with pathologically confirmed advanced cervical squamous carcinomas were enrolled in this prospective study. 3.0 T pelvic MR examinations including diffusion weighted imaging (b = 0, 800 s/mm 2 ) were performed before CCRT (pre-CCRT) and at the end of 2nd week of CCRT (mid-CCRT). ADC histogram and texture features were derived from the whole volume of cervical cancers. With a mean follow-up of 25 months (range, 11 ∼ 43), 10/36 (27.8%) patients ended with recurrence. Pre-CCRT 75th, 90th, correlation, autocorrelation and mid-CCRT ADC mean , 10th, 25th, 50th, 75th, 90th, autocorrelation can effectively differentiate the recurrence from nonrecurrence group with area under the curve ranging from 0.742 to 0.850 (P values range, 0.001 ∼ 0.038). Pre- and mid-treatment whole-lesion ADC histogram and texture analysis hold great potential in predicting tumor recurrence of advanced cervical cancer treated with CCRT.

Pulmonary emphysema classification based on an improved texton learning model by sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Fujita, Hiroshi

2013-03-01

In this paper, we present a texture classification method based on texton learned via sparse representation (SR) with new feature histogram maps in the classification of emphysema. First, an overcomplete dictionary of textons is learned via KSVD learning on every class image patches in the training dataset. In this stage, high-pass filter is introduced to exclude patches in smooth area to speed up the dictionary learning process. Second, 3D joint-SR coefficients and intensity histograms of the test images are used for characterizing regions of interest (ROIs) instead of conventional feature histograms constructed from SR coefficients of the test images over the dictionary. Classification is then performed using a classifier with distance as a histogram dissimilarity measure. Four hundreds and seventy annotated ROIs extracted from 14 test subjects, including 6 paraseptal emphysema (PSE) subjects, 5 centrilobular emphysema (CLE) subjects and 3 panlobular emphysema (PLE) subjects, are used to evaluate the effectiveness and robustness of the proposed method. The proposed method is tested on 167 PSE, 240 CLE and 63 PLE ROIs consisting of mild, moderate and severe pulmonary emphysema. The accuracy of the proposed system is around 74%, 88% and 89% for PSE, CLE and PLE, respectively.

Efficient reversible data hiding in encrypted image with public key cryptosystem

NASA Astrophysics Data System (ADS)

Xiang, Shijun; Luo, Xinrong

2017-12-01

This paper proposes a new reversible data hiding scheme for encrypted images by using homomorphic and probabilistic properties of Paillier cryptosystem. The proposed method can embed additional data directly into encrypted image without any preprocessing operations on original image. By selecting two pixels as a group for encryption, data hider can retrieve the absolute differences of groups of two pixels by employing a modular multiplicative inverse method. Additional data can be embedded into encrypted image by shifting histogram of the absolute differences by using the homomorphic property in encrypted domain. On the receiver side, legal user can extract the marked histogram in encrypted domain in the same way as data hiding procedure. Then, the hidden data can be extracted from the marked histogram and the encrypted version of original image can be restored by using inverse histogram shifting operations. Besides, the marked absolute differences can be computed after decryption for extraction of additional data and restoration of original image. Compared with previous state-of-the-art works, the proposed scheme can effectively avoid preprocessing operations before encryption and can efficiently embed and extract data in encrypted domain. The experiments on the standard image files also certify the effectiveness of the proposed scheme.

Air Traffic Sector Configuration Change Frequency

NASA Technical Reports Server (NTRS)

Chatterji, Gano Broto; Drew, Michael

2009-01-01

Several techniques for partitioning airspace have been developed in the literature. The question of whether a region of airspace created by such methods can be used with other days of traffic, and the number of times a different partition is needed during the day is examined in this paper. Both these aspects are examined for the Fort Worth Center airspace sectors. A Mixed Integer Linear Programming method is used with actual air traffic data of ten high-volume low-weather-delay days for creating sectors. Nine solutions were obtained for each two-hour period of the day by partitioning the center airspace into two through 18 sectors in steps of two sectors. Actual track-data were played back with the generated partitions for creating histograms of the traffic-counts. The best partition for each two-hour period was then identified based on the nine traffic-count distributions. Numbers of sectors in such partitions were analyzed to determine the number of times a different configuration is needed during the day. One to three partitions were selected for the 24-hour period, and traffic data from ten days were played back to test if the traffic-counts stayed below the threshold values associated with these partitions. Results show that these partitions are robust and can be used for longer durations than they were designed for

Background estimation and player detection in badminton video clips using histogram of pixel values along temporal dimension

NASA Astrophysics Data System (ADS)

Peng, Yahui; Ma, Xiao; Gao, Xinyu; Zhou, Fangxu

2015-12-01

Computer vision is an important tool for sports video processing. However, its application in badminton match analysis is very limited. In this study, we proposed a straightforward but robust histogram-based background estimation and player detection methods for badminton video clips, and compared the results with the naive averaging method and the mixture of Gaussians methods, respectively. The proposed method yielded better background estimation results than the naive averaging method and more accurate player detection results than the mixture of Gaussians player detection method. The preliminary results indicated that the proposed histogram-based method could estimate the background and extract the players accurately. We conclude that the proposed method can be used for badminton player tracking and further studies are warranted for automated match analysis.

Machine assisted histogram classification

NASA Astrophysics Data System (ADS)

Benyó, B.; Gaspar, C.; Somogyi, P.

2010-04-01

LHCb is one of the four major experiments under completion at the Large Hadron Collider (LHC). Monitoring the quality of the acquired data is important, because it allows the verification of the detector performance. Anomalies, such as missing values or unexpected distributions can be indicators of a malfunctioning detector, resulting in poor data quality. Spotting faulty or ageing components can be either done visually using instruments, such as the LHCb Histogram Presenter, or with the help of automated tools. In order to assist detector experts in handling the vast monitoring information resulting from the sheer size of the detector, we propose a graph based clustering tool combined with machine learning algorithm and demonstrate its use by processing histograms representing 2D hitmaps events. We prove the concept by detecting ion feedback events in the LHCb experiment's RICH subdetector.

Quantifying nonstationary radioactivity concentration fluctuations near Chernobyl: A complete statistical description

NASA Astrophysics Data System (ADS)

Viswanathan, G. M.; Buldyrev, S. V.; Garger, E. K.; Kashpur, V. A.; Lucena, L. S.; Shlyakhter, A.; Stanley, H. E.; Tschiersch, J.

2000-09-01

We analyze nonstationary 137Cs atmospheric activity concentration fluctuations measured near Chernobyl after the 1986 disaster and find three new results: (i) the histogram of fluctuations is well described by a log-normal distribution; (ii) there is a pronounced spectral component with period T=1yr, and (iii) the fluctuations are long-range correlated. These findings allow us to quantify two fundamental statistical properties of the data: the probability distribution and the correlation properties of the time series. We interpret our findings as evidence that the atmospheric radionuclide resuspension processes are tightly coupled to the surrounding ecosystems and to large time scale weather patterns.

WE-G-BRD-09: Prediction of Local Control/Failure by Using Feature Histogram Selection in Follow-Up T2-Weighted MR Image in Spinal Tumors After Stereotactic Body Radiation Therapy

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

Zhou, J; Harb, J; Jawad, M

2014-06-15

Purpose: In follow-up T2-weighted MR images of spinal tumor patients treated with stereotactic body radiation therapy (SBRT), high intensity features embedded in dark surroundings may suggest a local failure (LF). We investigated image intensity histogram in imaging features to predict LF and local control (LC). Methods: Sixty-seven spinal tumors were treated with SBRT at our institution with scheduled follow-up MR T2-weighted (TR 3200–6600ms; TE 75-132ms) imaging. The LF group included 10 tumors with 8.7 months median follow-up, while the LC group had 11 tumors with 24.1 months median follow-up. The follow-up images were fused to the planning CT. Image intensitymore » histograms of the GTV were calculated. Voxels in greater than 90% (V90), 80% (V80), and peak (Vpeak) of the histogram were grouped into sub-ROIs to determine the best feature histogram. The intensity of each sub-ROI was evaluated using the mean T2-weighted signal ratio (intensity in sub-ROI / intensity in normal vertebrae). An ROC curve in predicting LF for each sub-ROI was calculated to determine the best feature histogram parameter for LF prediction. Results: Mean T2-weighted signal ratio in the LF group was significantly higher than that in the LC group for all sub-ROIs (1.1±0.4 vs. 0.7±0.2, 1.2±0.4 vs. 0.8±0.2, 1.4±0.5 vs. 0.8±0.2, for V90, V80, and Vpeak, p=0.02, 0.02, and 0.002, respectively). The corresponding areas-under-curve (AUC) of ROC were 0.78, 0.80, and 0.87, p=0.02, 0.03, 0.004, respectively. No correlation was found between T2-weighted signal ratio in Vpeak and follow-up time (Pearson's ρ=0.15). Conclusion: Increased T2-weighted signal can be used to identify local failure while decreased signal indicates local control after spinal SBRT. By choosing the best histogram parameter (here the Vpeak), the AUC of the ROC can be substantially improved, which implies reliable prediction of LC and LF. These results are being further studied and validated with large multi-institutional data.« less

Characterization of Class A low-level radioactive waste 1986--1990. Volume 6: Appendices G--J

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

Dehmel, J.C.; Loomis, D.; Mauro, J.

1994-01-01

Under contract to the US Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, the firms of S. Cohen & Associates, Inc. (SC&A) and Eastern Research Group (ERG) have compiled a report that describes the physical, chemical, and radiological properties of Class-A low-level radioactive waste. The report also presents information characterizing various methods and facilities used to treat and dispose non-radioactive waste. A database management program was developed for use in accessing, sorting, analyzing, and displaying the electronic data provided by EG&G. The program was used to present and aggregate data characterizing the radiological, physical, and chemical properties of the wastemore » from descriptions contained in shipping manifests. The data thus retrieved are summarized in tables, histograms, and cumulative distribution curves presenting radionuclide concentration distributions in Class-A waste as a function of waste streams, by category of waste generators, and regions of the United States. The report also provides information characterizing methods and facilities used to treat and dispose non-radioactive waste, including industrial, municipal, and hazardous waste regulated under Subparts C and D of the Resource Conservation and Recovery Act (RCRA). The information includes a list of disposal options, the geographical locations of the processing and disposal facilities, and a description of the characteristics of such processing and disposal facilities. Volume 1 contains the Executive Summary, Volume 2 presents the Class-A waste database, Volume 3 presents the information characterizing non-radioactive waste management practices and facilities, and Volumes 4 through 7 contain Appendices A through P with supporting information.« less

Quantifying the Evolution of Melt Ponds in the Marginal Ice Zone Using High Resolution Optical Imagery and Neural Networks

NASA Astrophysics Data System (ADS)

Ortiz, M.; Pinales, J. C.; Graber, H. C.; Wilkinson, J.; Lund, B.

2016-02-01

Melt ponds on sea ice play a significant and complex role on the thermodynamics in the Marginal Ice Zone (MIZ). Ponding reduces the sea ice's ability to reflect sunlight, and in consequence, exacerbates the albedo positive feedback cycle. In order to understand how melt ponds work and their effect on the heat uptake of sea ice, we must quantify ponds through their seasonal evolution first. A semi-supervised neural network three-class learning scheme using a gradient descent with momentum and adaptive learning rate backpropagation function is applied to classify melt ponds/melt areas in the Beaufort Sea region. The network uses high resolution panchromatic satellite images from the MEDEA program, which are collocated with autonomous platform arrays from the Marginal Ice Zone Program, including ice mass-balance buoys, arctic weather stations and wave buoys. The goal of the study is to capture the spatial variation of melt onset and freeze-up of the ponds within the MIZ, and gather ponding statistics such as size and concentration. The innovation of this work comes from training the neural network as the melt ponds evolve over time; making the machine learning algorithm time-dependent, which has not been previously done. We will achieve this by analyzing the image histograms through quantification of the minima and maxima intensity changes as well as linking textural variation information of the imagery. We will compare the evolution of the melt ponds against several different array sites on the sea ice to explore if there are spatial differences among the separated platforms in the MIZ.

Mouse Curve Biometrics

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

Schulz, Douglas A.

2007-10-08

A biometric system suitable for validating user identity using only mouse movements and no specialized equipment is presented. Mouse curves (mouse movements with little or no pause between them) are individually classied and used to develop classication histograms, which are representative of an individual's typical mouse use. These classication histograms can then be compared to validate identity. This classication approach is suitable for providing continuous identity validation during an entire user session.

DIF Testing with an Empirical-Histogram Approximation of the Latent Density for Each Group

ERIC Educational Resources Information Center

Woods, Carol M.

2011-01-01

This research introduces, illustrates, and tests a variation of IRT-LR-DIF, called EH-DIF-2, in which the latent density for each group is estimated simultaneously with the item parameters as an empirical histogram (EH). IRT-LR-DIF is used to evaluate the degree to which items have different measurement properties for one group of people versus…

An Automated Energy Detection Algorithm Based on Kurtosis-Histogram Excision

DTIC Science & Technology

2018-01-01

ARL-TR-8269 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection Algorithm Based on Kurtosis-Histogram Excision...needed. Do not return it to the originator. ARL-TR-8269 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection...collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources

Liver fibrosis: in vivo evaluation using intravoxel incoherent motion-derived histogram metrics with histopathologic findings at 3.0 T.

PubMed

Hu, Fubi; Yang, Ru; Huang, Zixing; Wang, Min; Zhang, Hanmei; Yan, Xu; Song, Bin

2017-12-01

To retrospectively determine the feasibility of intravoxel incoherent motion (IVIM) imaging based on histogram analysis for the staging of liver fibrosis (LF) using histopathologic findings as the reference standard. 56 consecutive patients (14 men, 42 women; age range, 15-76, years) with chronic liver diseases (CLDs) were studied using IVIM-DWI with 9 b-values (0, 25, 50, 75, 100, 150, 200, 500, 800 s/mm 2 ) at 3.0 T. Fibrosis stage was evaluated using the METAVIR scoring system. Histogram metrics including mean, standard deviation (Std), skewness, kurtosis, minimum (Min), maximum (Max), range, interquartile (Iq) range, and percentiles (10, 25, 50, 75, 90th) were extracted from apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) maps. All histogram metrics among different fibrosis groups were compared using one-way analysis of variance or nonparametric Kruskal-Wallis test. For significant parameters, receivers operating characteristic curve (ROC) analyses were further performed for the staging of LF. Based on their METAVIR stage, the 56 patients were reclassified into three groups as follows: F0-1 group (n = 25), F2-3 group (n = 21), and F4 group (n = 10). The mean, Iq range, percentiles (50, 75, and 90th) of D* maps between the groups were significant differences (all P < 0.05). Area under the ROC curve (AUC) of the mean, Iq range, 50, 75, and 90th percentile of D* maps for identifying significant LF (≥F2 stage) was 0.901, 0.859, 0.876, 0.943, and 0.886 (all P < 0.0001), respectively; for diagnosing severe fibrosis or cirrhosis (F4), AUC was 0.917, 0.922, 0.943, 0.985, and 0.939 (all P < 0.0001), respectively. The histogram metrics of ADC, D, and f maps demonstrated no significant difference among the groups (all P > 0.05). Histogram analysis of D* map derived from IVIM can be used to stage liver fibrosis in patients with CLDs and provide more quantitative information beyond the mean value.

The impact of slice-reduced computed tomography on histogram-based densitometry assessment of lung fibrosis in patients with systemic sclerosis

PubMed Central

Maurer, Britta; Suliman, Yossra A.; Morsbach, Fabian; Distler, Oliver; Frauenfelder, Thomas

2018-01-01

Background To evaluate usability of slice-reduced sequential computed tomography (CT) compared to standard high-resolution CT (HRCT) in patients with systemic sclerosis (SSc) for qualitative and quantitative assessment of interstitial lung disease (ILD) with respect to (I) detection of lung parenchymal abnormalities, (II) qualitative and semiquantitative visual assessment, (III) quantification of ILD by histograms and (IV) accuracy for the 20%-cut off discrimination. Methods From standard chest HRCT of 60 SSc patients sequential 9-slice-computed tomography (reduced HRCT) was retrospectively reconstructed. ILD was assessed by visual scoring and quantitative histogram parameters. Results from standard and reduced HRCT were compared using non-parametric tests and analysed by univariate linear regression analyses. Results With respect to the detection of parenchymal abnormalities, only the detection of intrapulmonary bronchiectasis was significantly lower in reduced HRCT compared to standard HRCT (P=0.039). No differences were found comparing visual scores for fibrosis severity and extension from standard and reduced HRCT (P=0.051–0.073). All scores correlated significantly (P<0.001) to histogram parameters derived from both, standard and reduced HRCT. Significant higher values of kurtosis and skewness for reduced HRCT were found (both P<0.001). In contrast to standard HRCT histogram parameters from reduced HRCT showed significant discrimination at cut-off 20% fibrosis (sensitivity 88% kurtosis and skewness; specificity 81% kurtosis and 86% skewness; cut-off kurtosis ≤26, cut-off skewness ≤4; both P<0.001). Conclusions Reduced HRCT is a robust method to assess lung fibrosis in SSc with minimal radiation dose with no difference in scoring assessment of lung fibrosis severity and extension in comparison to standard HRCT. In contrast to standard HRCT histogram parameters derived from the approach of reduced HRCT could discriminate at a threshold of 20% lung fibrosis with high sensitivity and specificity. Hence it might be used to detect early disease progression of lung fibrosis in context of monitoring and treatment of SSc patients. PMID:29850118

Visual vs Fully Automatic Histogram-Based Assessment of Idiopathic Pulmonary Fibrosis (IPF) Progression Using Sequential Multidetector Computed Tomography (MDCT)

PubMed Central

Colombi, Davide; Dinkel, Julien; Weinheimer, Oliver; Obermayer, Berenike; Buzan, Teodora; Nabers, Diana; Bauer, Claudia; Oltmanns, Ute; Palmowski, Karin; Herth, Felix; Kauczor, Hans Ulrich; Sverzellati, Nicola

2015-01-01

Objectives To describe changes over time in extent of idiopathic pulmonary fibrosis (IPF) at multidetector computed tomography (MDCT) assessed by semi-quantitative visual scores (VSs) and fully automatic histogram-based quantitative evaluation and to test the relationship between these two methods of quantification. Methods Forty IPF patients (median age: 70 y, interquartile: 62-75 years; M:F, 33:7) that underwent 2 MDCT at different time points with a median interval of 13 months (interquartile: 10-17 months) were retrospectively evaluated. In-house software YACTA quantified automatically lung density histogram (10th-90th percentile in 5th percentile steps). Longitudinal changes in VSs and in the percentiles of attenuation histogram were obtained in 20 untreated patients and 20 patients treated with pirfenidone. Pearson correlation analysis was used to test the relationship between VSs and selected percentiles. Results In follow-up MDCT, visual overall extent of parenchymal abnormalities (OE) increased in median by 5 %/year (interquartile: 0 %/y; +11 %/y). Substantial difference was found between treated and untreated patients in HU changes of the 40th and of the 80th percentiles of density histogram. Correlation analysis between VSs and selected percentiles showed higher correlation between the changes (Δ) in OE and Δ 40th percentile (r=0.69; p<0.001) as compared to Δ 80th percentile (r=0.58; p<0.001); closer correlation was found between Δ ground-glass extent and Δ 40th percentile (r=0.66, p<0.001) as compared to Δ 80th percentile (r=0.47, p=0.002), while the Δ reticulations correlated better with the Δ 80th percentile (r=0.56, p<0.001) in comparison to Δ 40th percentile (r=0.43, p=0.003). Conclusions There is a relevant and fully automatically measurable difference at MDCT in VSs and in histogram analysis at one year follow-up of IPF patients, whether treated or untreated: Δ 40th percentile might reflect the change in overall extent of lung abnormalities, notably of ground-glass pattern; furthermore Δ 80th percentile might reveal the course of reticular opacities. PMID:26110421

Breast lesion characterization using whole-lesion histogram analysis with stretched-exponential diffusion model.

PubMed

Liu, Chunling; Wang, Kun; Li, Xiaodan; Zhang, Jine; Ding, Jie; Spuhler, Karl; Duong, Timothy; Liang, Changhong; Huang, Chuan

2018-06-01

Diffusion-weighted imaging (DWI) has been studied in breast imaging and can provide more information about diffusion, perfusion and other physiological interests than standard pulse sequences. The stretched-exponential model has previously been shown to be more reliable than conventional DWI techniques, but different diagnostic sensitivities were found from study to study. This work investigated the characteristics of whole-lesion histogram parameters derived from the stretched-exponential diffusion model for benign and malignant breast lesions, compared them with conventional apparent diffusion coefficient (ADC), and further determined which histogram metrics can be best used to differentiate malignant from benign lesions. This was a prospective study. Seventy females were included in the study. Multi-b value DWI was performed on a 1.5T scanner. Histogram parameters of whole lesions for distributed diffusion coefficient (DDC), heterogeneity index (α), and ADC were calculated by two radiologists and compared among benign lesions, ductal carcinoma in situ (DCIS), and invasive carcinoma confirmed by pathology. Nonparametric tests were performed for comparisons among invasive carcinoma, DCIS, and benign lesions. Comparisons of receiver operating characteristic (ROC) curves were performed to show the ability to discriminate malignant from benign lesions. The majority of histogram parameters (mean/min/max, skewness/kurtosis, 10-90 th percentile values) from DDC, α, and ADC were significantly different among invasive carcinoma, DCIS, and benign lesions. DDC 10% (area under curve [AUC] = 0.931), ADC 10% (AUC = 0.893), and α mean (AUC = 0.787) were found to be the best metrics in differentiating benign from malignant tumors among all histogram parameters derived from ADC and α, respectively. The combination of DDC 10% and α mean , using logistic regression, yielded the highest sensitivity (90.2%) and specificity (95.5%). DDC 10% and α mean derived from the stretched-exponential model provides more information and better diagnostic performance in differentiating malignancy from benign lesions than ADC parameters derived from a monoexponential model. 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1701-1710. © 2017 International Society for Magnetic Resonance in Medicine.

Quantitative computed tomography applied to interstitial lung diseases.

PubMed

Obert, Martin; Kampschulte, Marian; Limburg, Rebekka; Barańczuk, Stefan; Krombach, Gabriele A

2018-03-01

To evaluate a new image marker that retrieves information from computed tomography (CT) density histograms, with respect to classification properties between different lung parenchyma groups. Furthermore, to conduct a comparison of the new image marker with conventional markers. Density histograms from 220 different subjects (normal = 71; emphysema = 73; fibrotic = 76) were used to compare the conventionally applied emphysema index (EI), 15 th percentile value (PV), mean value (MV), variance (V), skewness (S), kurtosis (K), with a new histogram's functional shape (HFS) method. Multinomial logistic regression (MLR) analyses was performed to calculate predictions of different lung parenchyma group membership using the individual methods, as well as combinations thereof, as covariates. Overall correct assigned subjects (OCA), sensitivity (sens), specificity (spec), and Nagelkerke's pseudo R 2 (NR 2 ) effect size were estimated. NR 2 was used to set up a ranking list of the different methods. MLR indicates the highest classification power (OCA of 92%; sens 0.95; spec 0.89; NR 2 0.95) when all histogram analyses methods were applied together in the MLR. Highest classification power among individually applied methods was found using the HFS concept (OCA 86%; sens 0.93; spec 0.79; NR 2 0.80). Conventional methods achieved lower classification potential on their own: EI (OCA 69%; sens 0.95; spec 0.26; NR 2 0.52); PV (OCA 69%; sens 0.90; spec 0.37; NR 2 0.57); MV (OCA 65%; sens 0.71; spec 0.58; NR 2 0.61); V (OCA 66%; sens 0.72; spec 0.53; NR 2 0.66); S (OCA 65%; sens 0.88; spec 0.26; NR 2 0.55); and K (OCA 63%; sens 0.90; spec 0.16; NR 2 0.48). The HFS method, which was so far applied to a CT bone density curve analysis, is also a remarkable information extraction tool for lung density histograms. Presumably, being a principle mathematical approach, the HFS method can extract valuable health related information also from histograms from complete different areas. Copyright © 2018 Elsevier B.V. All rights reserved.

Performance evaluation of the Abbott CELL-DYN Emerald for use as a bench-top analyzer in a research setting.

PubMed

Khoo, T-L; Xiros, N; Guan, F; Orellana, D; Holst, J; Joshua, D E; Rasko, J E J

2013-08-01

The CELL-DYN Emerald is a compact bench-top hematology analyzer that can be used for a three-part white cell differential analysis. To determine its utility for analysis of human and mouse samples, we evaluated this machine against the larger CELL-DYN Sapphire and Sysmex XT2000iV hematology analyzers. 120 human (normal and abnormal) and 30 mouse (normal and abnormal) samples were analyzed on both the CELL-DYN Emerald and CELL-DYN Sapphire or Sysmex XT2000iV analyzers. For mouse samples, the CELL-DYN Emerald analyzer required manual recalibration based on the histogram populations. Analysis of the CELL-DYN Emerald showed excellent precision, within accepted ranges (white cell count CV% = 2.09%; hemoglobin CV% = 1.68%; platelets CV% = 4.13%). Linearity was excellent (R² ≥ 0.99), carryover was minimal (<1%), and overall interinstrument agreement was acceptable for both human and mouse samples. Comparison between the CELL-DYN Emerald and Sapphire analyzers for human samples or Sysmex XT2000iV analyzer for mouse samples showed excellent correlation for all parameters. The CELL-DYN Emerald was generally comparable to the larger reference analyzer for both human and mouse samples. It would be suitable for use in satellite research laboratories or as a backup system in larger laboratories. © 2012 John Wiley & Sons Ltd.

Response evaluation of giant-cell tumor of bone treated by denosumab: Histogram and texture analysis of CT images.

PubMed

Yi, Jisook; Lee, Young Han; Kim, Sang Kyum; Kim, Seung Hyun; Song, Ho-Taek; Shin, Kyoo-Ho; Suh, Jin-Suck

2018-05-01

This study aimed to compare computed tomography (CT) features, including tumor size and textural and histogram measurements, of giant-cell tumors of bone (GCTBs) before and after denosumab treatment and determine their applicability in monitoring GCTB response to denosumab treatment. This retrospective study included eight patients (male, 3; female, 5; mean age, 33.4 years) diagnosed with GCTB, who had received treatment by denosumab and had undergone pre- and post-treatment non-contrast CT between January 2010 and December 2016. This study was approved by the institutional review board. Pre- and post-treatment size, histogram, and textural parameters of GCTBs were compared by the Wilcoxon signed-rank test. Pathological findings of five patients who underwent surgery after denosumab treatment were evaluated for assessment of treatment response. Relative to the baseline values, the tumor size had decreased, while the mean attenuation, standard deviation, entropy (all, P = 0.017), and skewness (P = 0.036) of the GCTBs had significantly increased post-treatment. Although the difference was statistically insignificant, the tumors also exhibited increased kurtosis, contrast, and inverse difference moment (P = 0.123, 0.327, and 0.575, respectively) post-treatment. Histologic findings revealed new bone formation and complete depletion or decrease in the number of osteoclast-like giant cells. The histogram and textural parameters of GCTBs changed significantly after denosumab treatment. Knowledge of the tendency towards increased mean attenuation and heterogeneity but increased local homogeneity in post-treatment CT histogram and textural features of GCTBs might aid in treatment planning and tumor response evaluation during denosumab treatment. Copyright © 2018. Published by Elsevier B.V.

Comparative study of pulsed-continuous arterial spin labeling and dynamic susceptibility contrast imaging by histogram analysis in evaluation of glial tumors.

PubMed

Arisawa, Atsuko; Watanabe, Yoshiyuki; Tanaka, Hisashi; Takahashi, Hiroto; Matsuo, Chisato; Fujiwara, Takuya; Fujiwara, Masahiro; Fujimoto, Yasunori; Tomiyama, Noriyuki

2018-06-01

Arterial spin labeling (ASL) is a non-invasive perfusion technique that may be an alternative to dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) for assessment of brain tumors. To our knowledge, there have been no reports on histogram analysis of ASL. The purpose of this study was to determine whether ASL is comparable with DSC-MRI in terms of differentiating high-grade and low-grade gliomas by evaluating the histogram analysis of cerebral blood flow (CBF) in the entire tumor. Thirty-four patients with pathologically proven glioma underwent ASL and DSC-MRI. High-signal areas on contrast-enhanced T 1 -weighted images or high-intensity areas on fluid-attenuated inversion recovery images were designated as the volumes of interest (VOIs). ASL-CBF, DSC-CBF, and DSC-cerebral blood volume maps were constructed and co-registered to the VOI. Perfusion histogram analyses of the whole VOI and statistical analyses were performed to compare the ASL and DSC images. There was no significant difference in the mean values for any of the histogram metrics in both of the low-grade gliomas (n = 15) and the high-grade gliomas (n = 19). Strong correlations were seen in the 75th percentile, mean, median, and standard deviation values between the ASL and DSC images. The area under the curve values tended to be greater for the DSC images than for the ASL images. DSC-MRI is superior to ASL for distinguishing high-grade from low-grade glioma. ASL could be an alternative evaluation method when DSC-MRI cannot be used, e.g., in patients with renal failure, those in whom repeated examination is required, and in children.

Differentiation between malignant and benign thyroid nodules and stratification of papillary thyroid cancer with aggressive histological features: Whole-lesion diffusion-weighted imaging histogram analysis.

PubMed

Hao, Yonghong; Pan, Chu; Chen, WeiWei; Li, Tao; Zhu, WenZhen; Qi, JianPin

2016-12-01

To explore the usefulness of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (r-FOV) diffusion-weighted imaging (DWI) in differentiating malignant and benign thyroid nodules and stratifying papillary thyroid cancer (PTC) with aggressive histological features. This Institutional Review Board-approved, retrospective study included 93 patients with 101 pathologically proven thyroid nodules. All patients underwent preoperative r-FOV DWI at 3T. The whole-lesion ADC assessments were performed for each patient. Histogram-derived ADC parameters between different subgroups (pathologic type, extrathyroidal extension, lymph node metastasis) were compared. Receiver operating characteristic curve analysis was used to determine optimal histogram parameters in differentiating benign and malignant nodules and predicting aggressiveness of PTC. Mean ADC, median ADC, 5 th percentile ADC, 25 th percentile ADC, 75 th percentile ADC, 95 th percentile ADC (all P < 0.001), and kurtosis (P = 0.001) were significantly lower in malignant thyroid nodules, and mean ADC achieved the highest AUC (0.919) with a cutoff value of 1842.78 × 10 -6 mm 2 /s in differentiating malignant and benign nodules. Compared to the PTCs without extrathyroidal extension, PTCs with extrathyroidal extension showed significantly lower median ADC, 5 th percentile ADC, and 25 th percentile ADC. The 5 th percentile ADC achieved the highest AUC (0.757) with cutoff value of 911.5 × 10 -6 mm 2 /s for differentiating between PTCs with and without extrathyroidal extension. Whole-lesion ADC histogram analysis might help to differentiate malignant nodules from benign ones and show the PTCs with extrathyroidal extension. J. Magn. Reson. Imaging 2016;44:1546-1555. © 2016 International Society for Magnetic Resonance in Medicine.

Whole-tumor MRI histogram analyses of hepatocellular carcinoma: Correlations with Ki-67 labeling index.

PubMed

Hu, Xin-Xing; Yang, Zhao-Xia; Liang, He-Yue; Ding, Ying; Grimm, Robert; Fu, Cai-Xia; Liu, Hui; Yan, Xu; Ji, Yuan; Zeng, Meng-Su; Rao, Sheng-Xiang

2017-08-01

To evaluate whether whole-tumor histogram-derived parameters for an apparent diffusion coefficient (ADC) map and contrast-enhanced magnetic resonance imaging (MRI) could aid in assessing Ki-67 labeling index (LI) of hepatocellular carcinoma (HCC). In all, 57 patients with HCC who underwent pretreatment MRI with a 3T MR scanner were included retrospectively. Histogram parameters including mean, median, standard deviation, skewness, kurtosis, and percentiles (5 th , 25 th , 75 th , 95 th ) were derived from the ADC map and MR enhancement. Correlations between histogram parameters and Ki-67 LI were evaluated and differences between low Ki-67 (≤10%) and high Ki-67 (>10%) groups were assessed. Mean, median, 5 th , 25 th , 75 th percentiles of ADC, and mean, median, 25 th , 75 th , 95 th percentiles of enhancement of arterial phase (AP) demonstrated significant inverse correlations with Ki-67 LI (rho up to -0.48 for ADC, -0.43 for AP) and showed significant differences between low and high Ki-67 groups (P < 0.001-0.04). Areas under the receiver operator characteristics (ROC) curve for identification of high Ki-67 were 0.78, 0.77, 0.79, 0.82, and 0.76 for mean, median, 5 th , 25 th , 75 th percentiles of ADC, respectively, and 0.74, 0.81, 0.76, 0.82, 0.69 for mean, median, 25 th , 75 th , 95 th percentiles of AP, respectively. Histogram-derived parameters of ADC and AP were potentially helpful for predicting Ki-67 LI of HCC. 3 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;46:383-392. © 2016 International Society for Magnetic Resonance in Medicine.

Locally advanced rectal cancer: post-chemoradiotherapy ADC histogram analysis for predicting a complete response.

PubMed

Cho, Seung Hyun; Kim, Gab Chul; Jang, Yun-Jin; Ryeom, Hunkyu; Kim, Hye Jung; Shin, Kyung-Min; Park, Jun Seok; Choi, Gyu-Seog; Kim, See Hyung

2015-09-01

The value of diffusion-weighted imaging (DWI) for reliable differentiation between pathologic complete response (pCR) and residual tumor is still unclear. Recently, a few studies reported that histogram analysis can be helpful to monitor the therapeutic response in various cancer research. To investigate whether post-chemoradiotherapy (CRT) apparent diffusion coefficient (ADC) histogram analysis can be helpful to predict a pCR in locally advanced rectal cancer (LARC). Fifty patients who underwent preoperative CRT followed by surgery were enrolled in this retrospective study, non-pCR (n = 41) and pCR (n = 9), respectively. ADC histogram analysis encompassing the whole tumor was performed on two post-CRT ADC600 and ADC1000 (b factors 0, 600 vs. 0, 1000 s/mm(2)) maps. Mean, minimum, maximum, SD, mode, 10th, 25th, 50th, 75th, 90th percentile ADCs, skewness, and kurtosis were derived. Diagnostic performance for predicting pCR was evaluated and compared. On both maps, 10th and 25th ADCs showed better diagnostic performance than that using mean ADC. Tenth percentile ADCs revealed the best diagnostic performance on both ADC600 (AZ 0.841, sensitivity 100%, specificity 70.7%) and ADC1000 (AZ 0.821, sensitivity 77.8%, specificity 87.8%) maps. In comparison between 10th percentile and mean ADC, the specificity was significantly improved on both ADC600 (70.7% vs. 53.7%; P = 0.031) and ADC1000 (87.8% vs. 73.2%; P = 0.039) maps. Post-CRT ADC histogram analysis is helpful for predicting pCR in LARC, especially, in improving the specificity, compared with mean ADC. © The Foundation Acta Radiologica 2014.

A Whole-Tumor Histogram Analysis of Apparent Diffusion Coefficient Maps for Differentiating Thymic Carcinoma from Lymphoma.

PubMed

Zhang, Wei; Zhou, Yue; Xu, Xiao-Quan; Kong, Ling-Yan; Xu, Hai; Yu, Tong-Fu; Shi, Hai-Bin; Feng, Qing

2018-01-01

To assess the performance of a whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating thymic carcinoma from lymphoma, and compare it with that of a commonly used hot-spot region-of-interest (ROI)-based ADC measurement. Diffusion weighted imaging data of 15 patients with thymic carcinoma and 13 patients with lymphoma were retrospectively collected and processed with a mono-exponential model. ADC measurements were performed by using a histogram-based and hot-spot-ROI-based approach. In the histogram-based approach, the following parameters were generated: mean ADC (ADC mean ), median ADC (ADC median ), 10th and 90th percentile of ADC (ADC 10 and ADC 90 ), kurtosis, and skewness. The difference in ADCs between thymic carcinoma and lymphoma was compared using a t test. Receiver operating characteristic analyses were conducted to determine and compare the differentiating performance of ADCs. Lymphoma demonstrated significantly lower ADC mean , ADC median , ADC 10 , ADC 90 , and hot-spot-ROI-based mean ADC than those found in thymic carcinoma (all p values < 0.05). There were no differences found in the kurtosis ( p = 0.412) and skewness ( p = 0.273). The ADC 10 demonstrated optimal differentiating performance (cut-off value, 0.403 × 10 -3 mm 2 /s; area under the receiver operating characteristic curve [AUC], 0.977; sensitivity, 92.3%; specificity, 93.3%), followed by the ADC mean , ADC median , ADC 90 , and hot-spot-ROI-based mean ADC. The AUC of ADC 10 was significantly higher than that of the hot spot ROI based ADC (0.977 vs. 0.797, p = 0.036). Compared with the commonly used hot spot ROI based ADC measurement, a histogram analysis of ADC maps can improve the differentiating performance between thymic carcinoma and lymphoma.

Radiological indeterminate vestibular schwannoma and meningioma in cerebellopontine angle area: differentiating using whole-tumor histogram analysis of apparent diffusion coefficient.

PubMed

Xu, Xiao-Quan; Li, Yan; Hong, Xun-Ning; Wu, Fei-Yun; Shi, Hai-Bin

2017-02-01

To assess the role of whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating radiological indeterminate vestibular schwannoma (VS) from meningioma in cerebellopontine angle (CPA). Diffusion-weighted (DW) images (b = 0 and 1000 s/mm 2 ) of pathologically confirmed and radiological indeterminate CPA meningioma (CPAM) (n = 27) and VS (n = 12) were retrospectively collected and processed with mono-exponential model. Whole-tumor regions of interest were drawn on all slices of the ADC maps to obtain histogram parameters, including the mean ADC (ADC mean ), median ADC (ADC median ), 10th/25th/75th/90th percentile ADC (ADC 10 , ADC 25 , ADC 75 and ADC 90 ), skewness and kurtosis. The differences of ADC histogram parameters between CPAM and VS were compared using unpaired t-test. Multiple receiver operating characteristic (ROC) curves analysis was used to determine and compare the diagnostic value of each significant parameter. Significant differences were found on the ADC mean , ADC median , ADC 10 , ADC 25 , ADC 75 and ADC 90 between CPAM and VS (all p values < 0.001), while no significant difference was found on kurtosis (p = 0.562) and skewness (p = 0.047). ROC curves analysis revealed, a cut-off value of 1.126 × 10 -3 mm 2 /s for the ADC 90 value generated highest area under curves (AUC) for differentiating CPAM from VS (AUC, 0.975; sensitivity, 100%; specificity, 88.9%). Histogram analysis of ADC maps based on whole tumor can be a useful tool for differentiating radiological indeterminate CPAM from VS. The ADC 90 value was the most promising parameter for differentiating these two entities.

Atherogenic lipid phenotype in a general group of subjects.

PubMed

Van, Joanne; Pan, Jianqiu; Charles, M Arthur; Krauss, Ronald; Wong, Nathan; Wu, Xiaoshan

2007-11-01

The atherogenic lipid phenotype is a major cardiovascular risk factor, but normal values do not exist derived from 1 analysis in a general study group. To determine normal values of all of the atherogenic lipid phenotype parameters using subjects from a general study group. One hundred two general subjects were used to determine their atherogenic lipid phenotype using polyacrylamide gradient gels. Low-density lipoprotein (LDL) size revealed 24% of subjects express LDL phenotype B, defined as average LDL peak particle size 258 A or less; however, among the Chinese subjects, the expression of the B phenotype was higher at 44% (P = .02). For the total group, mean LDL size was 265 +/- 11 A (1 SD); however, histograms were bimodal in both men and women. After excluding subjects expressing LDL phenotype B, because they are at increased cardiovascular risk and thus are not completely healthy, LDL histograms were unimodal and the mean LDL size was 270 +/- 7 A. A small, dense LDL concentration histogram (total group) revealed skewing; thus, phenotype B subjects were excluded, for the rationale described previously, and the mean value was 13 +/- 9 mg/dL (0.33 +/- 0.23 mmol/L). High-density lipoprotein (HDL) cholesterol histograms were bimodal in both sexes. After removing subjects as described previously or if HDL cholesterol levels were less than 45 mg/dL, histograms were unimodal and revealed a mean HDL cholesterol value of 61 +/- 12 mg/dL (1.56 +/- 0.31 mmol/L). HDL 2, HDL 2a, and HDL 2b were similarly evaluated. Approximate normal values for the atherogenic lipid phenotype, similar to those derived from cardiovascular endpoint trials, can be determined if those high proportions of subjects with dyslipidemic cardiovascular risk are excluded.

Feasibility of histogram analysis of susceptibility-weighted MRI for staging of liver fibrosis

PubMed Central

Yang, Zhao-Xia; Liang, He-Yue; Hu, Xin-Xing; Huang, Ya-Qin; Ding, Ying; Yang, Shan; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-01-01

PURPOSE We aimed to evaluate whether histogram analysis of susceptibility-weighted imaging (SWI) could quantify liver fibrosis grade in patients with chronic liver disease (CLD). METHODS Fifty-three patients with CLD who underwent multi-echo SWI (TEs of 2.5, 5, and 10 ms) were included. Histogram analysis of SWI images were performed and mean, variance, skewness, kurtosis, and the 1st, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared. For significant parameters, further receiver operating characteristic (ROC) analyses were performed to evaluate the potential diagnostic performance for differentiating liver fibrosis stages. RESULTS The number of patients in each pathologic fibrosis grade was 7, 3, 5, 5, and 33 for F0, F1, F2, F3, and F4, respectively. The results of variance (TE: 10 ms), 90th percentile (TE: 10 ms), and 99th percentile (TE: 10 and 5 ms) in F0–F3 group were significantly lower than in F4 group, with areas under the ROC curves (AUCs) of 0.84 for variance and 0.70–0.73 for the 90th and 99th percentiles, respectively. The results of variance (TE: 10 and 5 ms), 99th percentile (TE: 10 ms), and skewness (TE: 2.5 and 5 ms) in F0–F2 group were smaller than those of F3/F4 group, with AUCs of 0.88 and 0.69 for variance (TE: 10 and 5 ms, respectively), 0.68 for 99th percentile (TE: 10 ms), and 0.73 and 0.68 for skewness (TE: 2.5 and 5 ms, respectively). CONCLUSION Magnetic resonance histogram analysis of SWI, particularly the variance, is promising for predicting advanced liver fibrosis and cirrhosis. PMID:27113421

Development of multichannel analyzer using sound card ADC for nuclear spectroscopy system

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

Ibrahim, Maslina Mohd; Yussup, Nolida; Lombigit, Lojius

This paper describes the development of Multi-Channel Analyzer (MCA) using sound card analogue to digital converter (ADC) for nuclear spectroscopy system. The system was divided into a hardware module and a software module. Hardware module consist of detector NaI (Tl) 2” by 2”, Pulse Shaping Amplifier (PSA) and a build in ADC chip from readily available in any computers’ sound system. The software module is divided into two parts which are a pre-processing of raw digital input and the development of the MCA software. Band-pass filter and baseline stabilization and correction were implemented for the pre-processing. For the MCA development,more » the pulse height analysis method was used to process the signal before displaying it using histogram technique. The development and tested result for using the sound card as an MCA are discussed.« less

Multiple objects tracking with HOGs matching in circular windows

NASA Astrophysics Data System (ADS)

Miramontes-Jaramillo, Daniel; Kober, Vitaly; Díaz-Ramírez, Víctor H.

2014-09-01

In recent years tracking applications with development of new technologies like smart TVs, Kinect, Google Glass and Oculus Rift become very important. When tracking uses a matching algorithm, a good prediction algorithm is required to reduce the search area for each object to be tracked as well as processing time. In this work, we analyze the performance of different tracking algorithms based on prediction and matching for a real-time tracking multiple objects. The used matching algorithm utilizes histograms of oriented gradients. It carries out matching in circular windows, and possesses rotation invariance and tolerance to viewpoint and scale changes. The proposed algorithm is implemented in a personal computer with GPU, and its performance is analyzed in terms of processing time in real scenarios. Such implementation takes advantage of current technologies and helps to process video sequences in real-time for tracking several objects at the same time.

Improving the convergence rate in affine registration of PET and SPECT brain images using histogram equalization.

PubMed

Salas-Gonzalez, D; Górriz, J M; Ramírez, J; Padilla, P; Illán, I A

2013-01-01

A procedure to improve the convergence rate for affine registration methods of medical brain images when the images differ greatly from the template is presented. The methodology is based on a histogram matching of the source images with respect to the reference brain template before proceeding with the affine registration. The preprocessed source brain images are spatially normalized to a template using a general affine model with 12 parameters. A sum of squared differences between the source images and the template is considered as objective function, and a Gauss-Newton optimization algorithm is used to find the minimum of the cost function. Using histogram equalization as a preprocessing step improves the convergence rate in the affine registration algorithm of brain images as we show in this work using SPECT and PET brain images.

HoDOr: histogram of differential orientations for rigid landmark tracking in medical images

NASA Astrophysics Data System (ADS)

Tiwari, Abhishek; Patwardhan, Kedar Anil

2018-03-01

Feature extraction plays a pivotal role in pattern recognition and matching. An ideal feature should be invariant to image transformations such as translation, rotation, scaling, etc. In this work, we present a novel rotation-invariant feature, which is based on Histogram of Oriented Gradients (HOG). We compare performance of the proposed approach with the HOG feature on 2D phantom data, as well as 3D medical imaging data. We have used traditional histogram comparison measures such as Bhattacharyya distance and Normalized Correlation Coefficient (NCC) to assess efficacy of the proposed approach under effects of image rotation. In our experiments, the proposed feature performs 40%, 20%, and 28% better than the HOG feature on phantom (2D), Computed Tomography (CT-3D), and Ultrasound (US-3D) data for image matching, and landmark tracking tasks respectively.

A novel parallel architecture for local histogram equalization

NASA Astrophysics Data System (ADS)

Ohannessian, Mesrob I.; Choueiter, Ghinwa F.; Diab, Hassan

2005-07-01

Local histogram equalization is an image enhancement algorithm that has found wide application in the pre-processing stage of areas such as computer vision, pattern recognition and medical imaging. The computationally intensive nature of the procedure, however, is a main limitation when real time interactive applications are in question. This work explores the possibility of performing parallel local histogram equalization, using an array of special purpose elementary processors, through an HDL implementation that targets FPGA or ASIC platforms. A novel parallelization scheme is presented and the corresponding architecture is derived. The algorithm is reduced to pixel-level operations. Processing elements are assigned image blocks, to maintain a reasonable performance-cost ratio. To further simplify both processor and memory organizations, a bit-serial access scheme is used. A brief performance assessment is provided to illustrate and quantify the merit of the approach.

Reducing Error Rates for Iris Image using higher Contrast in Normalization process

NASA Astrophysics Data System (ADS)

Aminu Ghali, Abdulrahman; Jamel, Sapiee; Abubakar Pindar, Zahraddeen; Hasssan Disina, Abdulkadir; Mat Daris, Mustafa

2017-08-01

Iris recognition system is the most secured, and faster means of identification and authentication. However, iris recognition system suffers a setback from blurring, low contrast and illumination due to low quality image which compromises the accuracy of the system. The acceptance or rejection rates of verified user depend solely on the quality of the image. In many cases, iris recognition system with low image contrast could falsely accept or reject user. Therefore this paper adopts Histogram Equalization Technique to address the problem of False Rejection Rate (FRR) and False Acceptance Rate (FAR) by enhancing the contrast of the iris image. A histogram equalization technique enhances the image quality and neutralizes the low contrast of the image at normalization stage. The experimental result shows that Histogram Equalization Technique has reduced FRR and FAR compared to the existing techniques.

Comparison between a new computer program and the reference software for gray-scale median analysis of atherosclerotic carotid plaques.

PubMed

Casella, Ivan Benaduce; Fukushima, Rodrigo Bono; Marques, Anita Battistini de Azevedo; Cury, Marcus Vinícius Martins; Presti, Calógero

2015-03-01

To compare a new dedicated software program and Adobe Photoshop for gray-scale median (GSM) analysis of B-mode images of carotid plaques. A series of 42 carotid plaques generating ≥50% diameter stenosis was evaluated by a single observer. The best segment for visualization of internal carotid artery plaque was identified on a single longitudinal view and images were recorded in JPEG format. Plaque analysis was performed by both programs. After normalization of image intensity (blood = 0, adventitial layer = 190), histograms were obtained after manual delineation of plaque. Results were compared with nonparametric Wilcoxon signed rank test and Kendall tau-b correlation analysis. GSM ranged from 00 to 100 with Adobe Photoshop and from 00 to 96 with IMTPC, with a high grade of similarity between image pairs, and a highly significant correlation (R = 0.94, p < .0001). IMTPC software appears suitable for the GSM analysis of carotid plaques. © 2014 Wiley Periodicals, Inc.

Novel algorithm and MATLAB-based program for automated power law analysis of single particle, time-dependent mean-square displacement

NASA Astrophysics Data System (ADS)

Umansky, Moti; Weihs, Daphne

2012-08-01

In many physical and biophysical studies, single-particle tracking is utilized to reveal interactions, diffusion coefficients, active modes of driving motion, dynamic local structure, micromechanics, and microrheology. The basic analysis applied to those data is to determine the time-dependent mean-square displacement (MSD) of particle trajectories and perform time- and ensemble-averaging of similar motions. The motion of particles typically exhibits time-dependent power-law scaling, and only trajectories with qualitatively and quantitatively comparable MSD should be ensembled. Ensemble averaging trajectories that arise from different mechanisms, e.g., actively driven and diffusive, is incorrect and can result inaccurate correlations between structure, mechanics, and activity. We have developed an algorithm to automatically and accurately determine power-law scaling of experimentally measured single-particle MSD. Trajectories can then categorized and grouped according to user defined cutoffs of time, amplitudes, scaling exponent values, or combinations. Power-law fits are then provided for each trajectory alongside categorized groups of trajectories, histograms of power laws, and the ensemble-averaged MSD of each group. The codes are designed to be easily incorporated into existing user codes. We expect that this algorithm and program will be invaluable to anyone performing single-particle tracking, be it in physical or biophysical systems. Catalogue identifier: AEMD_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEMD_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 25 892 No. of bytes in distributed program, including test data, etc.: 5 572 780 Distribution format: tar.gz Programming language: MATLAB (MathWorks Inc.) version 7.11 (2010b) or higher, program should also be backwards compatible. Symbolic Math Toolboxes (5.5) is required. The Curve Fitting Toolbox (3.0) is recommended. Computer: Tested on Windows only, yet should work on any computer running MATLAB. In Windows 7, should be used as administrator, if the user is not the administrator the program may not be able to save outputs and temporary outputs to all locations. Operating system: Any supporting MATLAB (MathWorks Inc.) v7.11 / 2010b or higher. Supplementary material: Sample output files (approx. 30 MBytes) are available. Classification: 12 External routines: Several MATLAB subfunctions (m-files), freely available on the web, were used as part of and included in, this code: count, NaN suite, parseArgs, roundsd, subaxis, wcov, wmean, and the executable pdfTK.exe. Nature of problem: In many physical and biophysical areas employing single-particle tracking, having the time-dependent power-laws governing the time-averaged meansquare displacement (MSD) of a single particle is crucial. Those power laws determine the mode-of-motion and hint at the underlying mechanisms driving motion. Accurate determination of the power laws that describe each trajectory will allow categorization into groups for further analysis of single trajectories or ensemble analysis, e.g. ensemble and time-averaged MSD. Solution method: The algorithm in the provided program automatically analyzes and fits time-dependent power laws to single particle trajectories, then group particles according to user defined cutoffs. It accepts time-dependent trajectories of several particles, each trajectory is run through the program, its time-averaged MSD is calculated, and power laws are determined in regions where the MSD is linear on a log-log scale. Our algorithm searches for high-curvature points in experimental data, here time-dependent MSD. Those serve as anchor points for determining the ranges of the power-law fits. Power-law scaling is then accurately determined and error estimations of the parameters and quality of fit are provided. After all single trajectory time-averaged MSDs are fit, we obtain cutoffs from the user to categorize and segment the power laws into groups; cutoff are either in exponents of the power laws, time of appearance of the fits, or both together. The trajectories are sorted according to the cutoffs and the time- and ensemble-averaged MSD of each group is provided, with histograms of the distributions of the exponents in each group. The program then allows the user to generate new trajectory files with trajectories segmented according to the determined groups, for any further required analysis. Additional comments: README file giving the names and a brief description of all the files that make-up the package and clear instructions on the installation and execution of the program is included in the distribution package. Running time: On an i5 Windows 7 machine with 4 GB RAM the automated parts of the run (excluding data loading and user input) take less than 45 minutes to analyze and save all stages for an 844 trajectory file, including optional PDF save. Trajectory length did not affect run time (tested up to 3600 frames/trajectory), which was on average 3.2±0.4 seconds per trajectory.

Landmark Detection in Orbital Images Using Salience Histograms

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Panetta, Julian; Schorghofer, Norbert; Greeley, Ronald; PendletonHoffer, Mary; bunte, Melissa

2010-01-01

NASA's planetary missions have collected, and continue to collect, massive volumes of orbital imagery. The volume is such that it is difficult to manually review all of the data and determine its significance. As a result, images are indexed and searchable by location and date but generally not by their content. A new automated method analyzes images and identifies "landmarks," or visually salient features such as gullies, craters, dust devil tracks, and the like. This technique uses a statistical measure of salience derived from information theory, so it is not associated with any specific landmark type. It identifies regions that are unusual or that stand out from their surroundings, so the resulting landmarks are context-sensitive areas that can be used to recognize the same area when it is encountered again. A machine learning classifier is used to identify the type of each discovered landmark. Using a specified window size, an intensity histogram is computed for each such window within the larger image (sliding the window across the image). Next, a salience map is computed that specifies, for each pixel, the salience of the window centered at that pixel. The salience map is thresholded to identify landmark contours (polygons) using the upper quartile of salience values. Descriptive attributes are extracted for each landmark polygon: size, perimeter, mean intensity, standard deviation of intensity, and shape features derived from an ellipse fit.

Distributions-per-level: a means of testing level detectors and models of patch-clamp data.

PubMed

Schröder, I; Huth, T; Suitchmezian, V; Jarosik, J; Schnell, S; Hansen, U P

2004-01-01

Level or jump detectors generate the reconstructed time series from a noisy record of patch-clamp current. The reconstructed time series is used to create dwell-time histograms for the kinetic analysis of the Markov model of the investigated ion channel. It is shown here that some additional lines in the software of such a detector can provide a powerful new means of patch-clamp analysis. For each current level that can be recognized by the detector, an array is declared. The new software assigns every data point of the original time series to the array that belongs to the actual state of the detector. From the data sets in these arrays distributions-per-level are generated. Simulated and experimental time series analyzed by Hinkley detectors are used to demonstrate the benefits of these distributions-per-level. First, they can serve as a test of the reliability of jump and level detectors. Second, they can reveal beta distributions as resulting from fast gating that would usually be hidden in the overall amplitude histogram. Probably the most valuable feature is that the malfunctions of the Hinkley detectors turn out to depend on the Markov model of the ion channel. Thus, the errors revealed by the distributions-per-level can be used to distinguish between different putative Markov models of the measured time series.

Accurate analysis and visualization of cardiac (11)C-PIB uptake in amyloidosis with semiautomatic software.

PubMed

Kero, Tanja; Lindsjö, Lars; Sörensen, Jens; Lubberink, Mark

2016-08-01

(11)C-PIB PET is a promising non-invasive diagnostic tool for cardiac amyloidosis. Semiautomatic analysis of PET data is now available but it is not known how accurate these methods are for amyloid imaging. The aim of this study was to evaluate the feasibility of one semiautomatic software tool for analysis and visualization of (11)C-PIB left ventricular retention index (RI) in cardiac amyloidosis. Patients with systemic amyloidosis and cardiac involvement (n = 10) and healthy controls (n = 5) were investigated with dynamic (11)C-PIB PET. Two observers analyzed the PET studies with semiautomatic software to calculate the left ventricular RI of (11)C-PIB and to create parametric images. The mean RI at 15-25 min from the semiautomatic analysis was compared with RI based on manual analysis and showed comparable values (0.056 vs 0.054 min(-1) for amyloidosis patients and 0.024 vs 0.025 min(-1) in healthy controls; P = .78) and the correlation was excellent (r = 0.98). Inter-reader reproducibility also was excellent (intraclass correlation coefficient, ICC > 0.98). Parametric polarmaps and histograms made visual separation of amyloidosis patients and healthy controls fast and simple. Accurate semiautomatic analysis of cardiac (11)C-PIB RI in amyloidosis patients is feasible. Parametric polarmaps and histograms make visual interpretation fast and simple.

Use of the transect method in satellite survey missions with application to the infrared astronomical satellite /IRAS/

NASA Technical Reports Server (NTRS)

Mclaughlin, W. I.; Lundy, S. A.; Ling, H. Y.; Stroberg, M. W.

1980-01-01

The coverage of the celestial sphere or the surface of the earth with a narrow-field instrument onboard a satellite can be described by a set of swaths on the sphere. A transect is a curve on this sphere constructed to sample the coverage. At each point on the transect the number of times that the field-of-view of the instrument has passed over the point is recorded. This information is conveniently displayed as an integer-valued histogram over the length of the transect. The effectiveness of the transect method for a particular observing plan and the best placement of the transects depends upon the structure of the set of observations. Survey missions are usually characterized by a somewhat parallel alignment of the instrument swaths. Using autocorrelation and cross-correlation functions among the histograms the structure of a survey has been analyzed into two components, and each is illustrated by a simple mathematical model. The complex, all-sky survey to be performed by the Infrared Astronomical Satellite (IRAS) is synthesized in some detail utilizing the objectives and constraints of that mission. It is seen that this survey possesses the components predicted by the simple models and this information is useful in characterizing the properties of the IRAS survey and the placement of the transects as a function of celestial latitude and certain structural properties of the coverage.

Automated quantitative muscle biopsy analysis system

NASA Technical Reports Server (NTRS)

Castleman, Kenneth R. (Inventor)

1980-01-01

An automated system to aid the diagnosis of neuromuscular diseases by producing fiber size histograms utilizing histochemically stained muscle biopsy tissue. Televised images of the microscopic fibers are processed electronically by a multi-microprocessor computer, which isolates, measures, and classifies the fibers and displays the fiber size distribution. The architecture of the multi-microprocessor computer, which is iterated to any required degree of complexity, features a series of individual microprocessors P.sub.n each receiving data from a shared memory M.sub.n-1 and outputing processed data to a separate shared memory M.sub.n+1 under control of a program stored in dedicated memory M.sub.n.

METEOSAT studies of clouds and radiation budget

NASA Technical Reports Server (NTRS)

Saunders, R. W.

1982-01-01

Radiation budget studies of the atmosphere/surface system from Meteosat, cloud parameter determination from space, and sea surface temperature measurements from TIROS N data are all described. This work was carried out on the interactive planetary image processing system (IPIPS), which allows interactive manipulationion of the image data in addition to the conventional computational tasks. The current hardware configuration of IPIPS is shown. The I(2)S is the principal interactive display allowing interaction via a trackball, four buttons under program control, or a touch tablet. Simple image processing operations such as contrast enhancing, pseudocoloring, histogram equalization, and multispectral combinations, can all be executed at the push of a button.

Chest CT window settings with multiscale adaptive histogram equalization: pilot study.

PubMed

Fayad, Laura M; Jin, Yinpeng; Laine, Andrew F; Berkmen, Yahya M; Pearson, Gregory D; Freedman, Benjamin; Van Heertum, Ronald

2002-06-01

Multiscale adaptive histogram equalization (MAHE), a wavelet-based algorithm, was investigated as a method of automatic simultaneous display of the full dynamic contrast range of a computed tomographic image. Interpretation times were significantly lower for MAHE-enhanced images compared with those for conventionally displayed images. Diagnostic accuracy, however, was insufficient in this pilot study to allow recommendation of MAHE as a replacement for conventional window display.

[The value of spectral frequency analysis by Doppler examination (author's transl)].

PubMed

Boccalon, H; Reggi, M; Lozes, A; Canal, C; Jausseran, J M; Courbier, R; Puel, P; Enjalbert, A

1981-01-01

Arterial stenoses of moderate extent may involve modifications of the blood flow. Arterial shading is not always examined at the best incident angle to assess the extent of the stenosis. Spectral frequency analysis by Doppler examination is a good means of evaluating the effect of moderate arterial lesions. The present study was carried out with a Doppler effect having an acoustic spectrum, which is shown in a histogram having 16 frequency bands. The values were recorded on the two femoral arteries. A study was also made of 49 normal subjects so as to establish a normal envelope histogram, taking into account the following parameters: maximum peak (800 Hz), low cut-off frequency (420 Hz), high cut-off frequency (2,600 Hz); the first peak was found to be present in 81 % of the subjects (at 375 Hz) and the second peak in 75 % of the subjects (2,020 Hz). Thirteen patients with iliac lesions of different extent were included in the study; details of these lesions were established in all cases by aortography. None of the recorded frequency histograms were located within the normal envelope. Two cases of moderate iliac stenoses were noted ( Less Than 50 % of the diameter) which interfered with the histogram, even though the femoral velocity signal was normal.

Differentially Private Histogram Publication For Dynamic Datasets: An Adaptive Sampling Approach

PubMed Central

Li, Haoran; Jiang, Xiaoqian; Xiong, Li; Liu, Jinfei

2016-01-01

Differential privacy has recently become a de facto standard for private statistical data release. Many algorithms have been proposed to generate differentially private histograms or synthetic data. However, most of them focus on “one-time” release of a static dataset and do not adequately address the increasing need of releasing series of dynamic datasets in real time. A straightforward application of existing histogram methods on each snapshot of such dynamic datasets will incur high accumulated error due to the composibility of differential privacy and correlations or overlapping users between the snapshots. In this paper, we address the problem of releasing series of dynamic datasets in real time with differential privacy, using a novel adaptive distance-based sampling approach. Our first method, DSFT, uses a fixed distance threshold and releases a differentially private histogram only when the current snapshot is sufficiently different from the previous one, i.e., with a distance greater than a predefined threshold. Our second method, DSAT, further improves DSFT and uses a dynamic threshold adaptively adjusted by a feedback control mechanism to capture the data dynamics. Extensive experiments on real and synthetic datasets demonstrate that our approach achieves better utility than baseline methods and existing state-of-the-art methods. PMID:26973795

Multi-site Study of Diffusion Metric Variability: Characterizing the Effects of Site, Vendor, Field Strength, and Echo Time using the Histogram Distance.

PubMed

Helmer, K G; Chou, M-C; Preciado, R I; Gimi, B; Rollins, N K; Song, A; Turner, J; Mori, S

2016-02-27

MRI-based multi-site trials now routinely include some form of diffusion-weighted imaging (DWI) in their protocol. These studies can include data originating from scanners built by different vendors, each with their own set of unique protocol restrictions, including restrictions on the number of available gradient directions, whether an externally-generated list of gradient directions can be used, and restrictions on the echo time (TE). One challenge of multi-site studies is to create a common imaging protocol that will result in a reliable and accurate set of diffusion metrics. The present study describes the effect of site, scanner vendor, field strength, and TE on two common metrics: the first moment of the diffusion tensor field (mean diffusivity, MD), and the fractional anisotropy (FA). We have shown in earlier work that ROI metrics and the mean of MD and FA histograms are not sufficiently sensitive for use in site characterization. Here we use the distance between whole brain histograms of FA and MD to investigate within- and between-site effects. We concluded that the variability of DTI metrics due to site, vendor, field strength, and echo time could influence the results in multi-center trials and that histogram distance is sensitive metrics for each of these variables.

Predicting the nodal status in gastric cancers: The role of apparent diffusion coefficient histogram characteristic analysis.

PubMed

Liu, Song; Zhang, Yujuan; Xia, Jie; Chen, Ling; Guan, Wenxian; Guan, Yue; Ge, Yun; He, Jian; Zhou, Zhengyang

2017-10-01

To explore the application of histogram analysis in preoperative T and N staging of gastric cancers, with a focus on characteristic parameters of apparent diffusion coefficient (ADC) maps. Eighty-seven patients with gastric cancers underwent diffusion weighted magnetic resonance imaging (b=0, 1000s/mm 2 ), which generated ADC maps. Whole-volume histogram analysis was performed on ADC maps and 7 characteristic parameters were obtained. All those patients underwent surgery and postoperative pathologic T and N stages were determined. Four parameters, including skew, kurtosis, s-sD av and sample number, showed significant differences among gastric cancers at different T and N stages. Most parameters correlated with T and N stages significantly and worked in differentiating gastric cancers at different T or N stages. Especially skew yielded a sensitivity of 0.758, a specificity of 0.810, and an area under the curve (AUC) of 0.802 for differentiating gastric cancers with and without lymph node metastasis (P<0.001). All the parameters, except AUC low , showed good or excellent inter-observer agreement with intra-class correlation coefficients ranging from 0.710 to 0.991. Characteristic parameters derived from whole-volume ADC histogram analysis could help assessing preoperative T and N stages of gastric cancers. Copyright © 2017. Published by Elsevier Inc.

Universal and adapted vocabularies for generic visual categorization.

PubMed

Perronnin, Florent

2008-07-01

Generic Visual Categorization (GVC) is the pattern classification problem which consists in assigning labels to an image based on its semantic content. This is a challenging task as one has to deal with inherent object/scene variations as well as changes in viewpoint, lighting and occlusion. Several state-of-the-art GVC systems use a vocabulary of visual terms to characterize images with a histogram of visual word counts. We propose a novel practical approach to GVC based on a universal vocabulary, which describes the content of all the considered classes of images, and class vocabularies obtained through the adaptation of the universal vocabulary using class-specific data. The main novelty is that an image is characterized by a set of histograms - one per class - where each histogram describes whether the image content is best modeled by the universal vocabulary or the corresponding class vocabulary. This framework is applied to two types of local image features: low-level descriptors such as the popular SIFT and high-level histograms of word co-occurrences in a spatial neighborhood. It is shown experimentally on two challenging datasets (an in-house database of 19 categories and the PASCAL VOC 2006 dataset) that the proposed approach exhibits state-of-the-art performance at a modest computational cost.

Statistical Properties of Line Centroid Velocity Increments in the rho Ophiuchi Cloud

NASA Technical Reports Server (NTRS)

Lis, D. C.; Keene, Jocelyn; Li, Y.; Phillips, T. G.; Pety, J.

1998-01-01

We present a comparison of histograms of CO (2-1) line centroid velocity increments in the rho Ophiuchi molecular cloud with those computed for spectra synthesized from a three-dimensional, compressible, but non-starforming and non-gravitating hydrodynamic simulation. Histograms of centroid velocity increments in the rho Ophiuchi cloud show clearly non-Gaussian wings, similar to those found in histograms of velocity increments and derivatives in experimental studies of laboratory and atmospheric flows, as well as numerical simulations of turbulence. The magnitude of these wings increases monotonically with decreasing separation, down to the angular resolution of the data. This behavior is consistent with that found in the phase of the simulation which has most of the properties of incompressible turbulence. The time evolution of the magnitude of the non-Gaussian wings in the histograms of centroid velocity increments in the simulation is consistent with the evolution of the vorticity in the flow. However, we cannot exclude the possibility that the wings are associated with the shock interaction regions. Moreover, in an active starforming region like the rho Ophiuchi cloud, the effects of shocks may be more important than in the simulation. However, being able to identify shock interaction regions in the interstellar medium is also important, since numerical simulations show that vorticity is generated in shock interactions.

Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization

PubMed Central

Chiu, Chung-Cheng; Ting, Chih-Chung

2016-01-01

Image enhancement methods have been widely used to improve the visual effects of images. Owing to its simplicity and effectiveness histogram equalization (HE) is one of the methods used for enhancing image contrast. However, HE may result in over-enhancement and feature loss problems that lead to unnatural look and loss of details in the processed images. Researchers have proposed various HE-based methods to solve the over-enhancement problem; however, they have largely ignored the feature loss problem. Therefore, a contrast enhancement algorithm based on gap adjustment for histogram equalization (CegaHE) is proposed. It refers to a visual contrast enhancement algorithm based on histogram equalization (VCEA), which generates visually pleasing enhanced images, and improves the enhancement effects of VCEA. CegaHE adjusts the gaps between two gray values based on the adjustment equation, which takes the properties of human visual perception into consideration, to solve the over-enhancement problem. Besides, it also alleviates the feature loss problem and further enhances the textures in the dark regions of the images to improve the quality of the processed images for human visual perception. Experimental results demonstrate that CegaHE is a reliable method for contrast enhancement and that it significantly outperforms VCEA and other methods. PMID:27338412

Analysis of dose heterogeneity using a subvolume-DVH

NASA Astrophysics Data System (ADS)

Said, M.; Nilsson, P.; Ceberg, C.

2017-11-01

The dose-volume histogram (DVH) is universally used in radiation therapy for its highly efficient way of summarizing three-dimensional dose distributions. An apparent limitation that is inherent to standard histograms is the loss of spatial information, e.g. it is no longer possible to tell where low- and high-dose regions are, and whether they are connected or disjoint. Two methods for overcoming the spatial fragmentation of low- and high-dose regions are presented, both based on the gray-level size zone matrix, which is a two-dimensional histogram describing the frequencies of connected regions of similar intensities. The first approach is a quantitative metric which can be likened to a homogeneity index. The large cold spot metric (LCS) is here defined to emphasize large contiguous regions receiving too low a dose; emphasis is put on both size, and deviation from the prescribed dose. In contrast, the subvolume-DVH (sDVH) is an extension to the standard DVH and allows for a qualitative evaluation of the degree of dose heterogeneity. The information retained from the two-dimensional histogram is overlaid on top of the DVH and the two are presented simultaneously. Both methods gauge the underlying heterogeneity in ways that the DVH alone cannot, and both have their own merits—the sDVH being more intuitive and the LCS being quantitative.

Digital image classification with the help of artificial neural network by simple histogram.

PubMed

Dey, Pranab; Banerjee, Nirmalya; Kaur, Rajwant

2016-01-01

Visual image classification is a great challenge to the cytopathologist in routine day-to-day work. Artificial neural network (ANN) may be helpful in this matter. In this study, we have tried to classify digital images of malignant and benign cells in effusion cytology smear with the help of simple histogram data and ANN. A total of 404 digital images consisting of 168 benign cells and 236 malignant cells were selected for this study. The simple histogram data was extracted from these digital images and an ANN was constructed with the help of Neurointelligence software [Alyuda Neurointelligence 2.2 (577), Cupertino, California, USA]. The network architecture was 6-3-1. The images were classified as training set (281), validation set (63), and test set (60). The on-line backpropagation training algorithm was used for this study. A total of 10,000 iterations were done to train the ANN system with the speed of 609.81/s. After the adequate training of this ANN model, the system was able to identify all 34 malignant cell images and 24 out of 26 benign cells. The ANN model can be used for the identification of the individual malignant cells with the help of simple histogram data. This study will be helpful in the future to identify malignant cells in unknown situations.

Short-term stability of T1 and T2 relaxation measures in multiple sclerosis normal appearing white matter.

PubMed

Liang, Alice L W; Vavasour, Irene M; Mädler, Burkhard; Traboulsee, Anthony L; Lang, Donna J; Li, David K B; MacKay, Alex L; Laule, Cornelia

2012-06-01

The presence of diffuse and widespread abnormalities within the 'normal appearing' white matter (NAWM) of multiple sclerosis (MS) brain has been established. T(1) histogram analysis has revealed increased T(1) (related to water content) in segmented NAWM, while quantitative assessment of T(2) relaxation measures has demonstrated decreased myelin water fraction (MWF, related to myelin content) and increased geometric mean T(2) (GMT(2)) of the intra/extracellular water pool. Previous studies with follow-up periods of 1-5 years have demonstrated longitudinal changes in T(1) histogram metrics over time; however, longitudinal changes in MWF and GMT(2) of segmented NAWM have not been examined. We examined the short-term evolution of MWF, GMT(2) and T(1) in MS NAWM based on monthly scanning over 6 months in 18 relapsing remitting (RR) MS subjects. Histogram metrics demonstrated short-term stability of T(1), MWF and remitting (RR) MS subjects. We observed no change in MWF, GMT(2) or T(1) histogram metrics in NAWM in RRMS over the course of 6 months. Longer follow-up periods may be required to establish demonstrable changes in NAWM based on of MWF, GMT(2) and T(1) metrics.

A program for the calculation of paraboloidal-dish solar thermal power plant performance

NASA Technical Reports Server (NTRS)

Bowyer, J. M., Jr.

1985-01-01

A program capable of calculating the design-point and quasi-steady-state annual performance of a paraboloidal-concentrator solar thermal power plant without energy storage was written for a programmable calculator equipped with suitable printer. The power plant may be located at any site for which a histogram of annual direct normal insolation is available. Inputs required by the program are aperture area and the design and annual efficiencies of the concentrator; the intercept factor and apparent efficiency of the power conversion subsystem and a polynomial representation of its normalized part-load efficiency; the efficiency of the electrical generator or alternator; the efficiency of the electric power conditioning and transport subsystem; and the fractional parasitic loses for the plant. Losses to auxiliaries associated with each individual module are to be deducted when the power conversion subsystem efficiencies are calculated. Outputs provided by the program are the system design efficiency, the annualized receiver efficiency, the annualized power conversion subsystem efficiency, total annual direct normal insolation received per unit area of concentrator aperture, and the system annual efficiency.

Gray-level transformations for interactive image enhancement. M.S. Thesis. Final Technical Report

NASA Technical Reports Server (NTRS)

Fittes, B. A.

1975-01-01

A gray-level transformation method suitable for interactive image enhancement was presented. It is shown that the well-known histogram equalization approach is a special case of this method. A technique for improving the uniformity of a histogram is also developed. Experimental results which illustrate the capabilities of both algorithms are described. Two proposals for implementing gray-level transformations in a real-time interactive image enhancement system are also presented.

[A fast iterative algorithm for adaptive histogram equalization].

PubMed

Cao, X; Liu, X; Deng, Z; Jiang, D; Zheng, C

1997-01-01

In this paper, we propose an iterative algorthm called FAHE., which is based on the relativity between the current local histogram and the one before the sliding window moving. Comparing with the basic AHE, the computing time of FAHE is decreased from 5 hours to 4 minutes on a 486dx/33 compatible computer, when using a 65 x 65 sliding window for a 512 x 512 with 8 bits gray-level range.

Ocean Wave Slope Statistics from Automated Analysis of Sun Glitter Photographs

DTIC Science & Technology

1985-06-01

8217*.... . .. , .. . .. I 1 SCONTROL MAPCROSSREF.LAdEf_ 2 Si4OuTINE HDSPLY ( HTST . No NAME. XO. XSTEPI 3 C 4 C SIUBROUTINE TO nISPLAY A UNIVARIATE HISTOGRAM...LYRANON. CSC, FESRUARV ?6s 1qA0. 7 C a C HTST z HISTOGRAM ARRAY. 9 C NT 0 ROW DIMFNSION OF HIST. to C N.1 x COLUMN DIMENSTnN OF MIST. it C 12 REAL HIST

Information-Adaptive Image Encoding and Restoration

NASA Technical Reports Server (NTRS)

Park, Stephen K.; Rahman, Zia-ur

1998-01-01

The multiscale retinex with color restoration (MSRCR) has shown itself to be a very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition. A number of algorithms exist that provide one or more of these features, but not all. In this paper we compare the performance of the MSRCR with techniques that are widely used for image enhancement. Specifically, we compare the MSRCR with color adjustment methods such as gamma correction and gain/offset application, histogram modification techniques such as histogram equalization and manual histogram adjustment, and other more powerful techniques such as homomorphic filtering and 'burning and dodging'. The comparison is carried out by testing the suite of image enhancement methods on a set of diverse images. We find that though some of these techniques work well for some of these images, only the MSRCR performs universally well oil the test set.

Sample Training Based Wildfire Segmentation by 2D Histogram θ-Division with Minimum Error

PubMed Central

Dong, Erqian; Sun, Mingui; Jia, Wenyan; Zhang, Dengyi; Yuan, Zhiyong

2013-01-01

A novel wildfire segmentation algorithm is proposed with the help of sample training based 2D histogram θ-division and minimum error. Based on minimum error principle and 2D color histogram, the θ-division methods were presented recently, but application of prior knowledge on them has not been explored. For the specific problem of wildfire segmentation, we collect sample images with manually labeled fire pixels. Then we define the probability function of error division to evaluate θ-division segmentations, and the optimal angle θ is determined by sample training. Performances in different color channels are compared, and the suitable channel is selected. To further improve the accuracy, the combination approach is presented with both θ-division and other segmentation methods such as GMM. Our approach is tested on real images, and the experiments prove its efficiency for wildfire segmentation. PMID:23878526

Histograms showing variations in oil yield, water yield, and specific gravity of oil from Fischer assay analyses of oil-shale drill cores and cuttings from the Piceance Basin, northwestern Colorado

USGS Publications Warehouse

Dietrich, John D.; Brownfield, Michael E.; Johnson, Ronald C.; Mercier, Tracey J.

2014-01-01

Recent studies indicate that the Piceance Basin in northwestern Colorado contains over 1.5 trillion barrels of oil in place, making the basin the largest known oil-shale deposit in the world. Previously published histograms display oil-yield variations with depth and widely correlate rich and lean oil-shale beds and zones throughout the basin. Histograms in this report display oil-yield data plotted alongside either water-yield or oil specific-gravity data. Fischer assay analyses of core and cutting samples collected from exploration drill holes penetrating the Eocene Green River Formation in the Piceance Basin can aid in determining the origins of those deposits, as well as estimating the amount of organic matter, halite, nahcolite, and water-bearing minerals. This report focuses only on the oil yield plotted against water yield and oil specific gravity.

A Comparison of the Multiscale Retinex With Other Image Enhancement Techniques

NASA Technical Reports Server (NTRS)

Rahman, Zia-Ur; Woodell, Glenn A.; Jobson, Daniel J.

1997-01-01

The multiscale retinex with color restoration (MSRCR) has shown itself to be a very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition. A number of algorithms exist that provide one or more of these features, but not all. In this paper we compare the performance of the MSRCR with techniques that are widely used for image enhancement. Specifically, we compare the MSRCR with color adjustment methods such as gamma correction and gain/offset application, histogram modification techniques such as histogram equalization and manual histogram adjustment, and other more powerful techniques such as homomorphic filtering and 'burning and dodging'. The comparison is carried out by testing the suite of image enhancement methods on a set of diverse images. We find that though some of these techniques work well for some of these images, only the MSRCR performs universally well on the test set.

Lindemann histograms as a new method to analyse nano-patterns and phases

NASA Astrophysics Data System (ADS)

Makey, Ghaith; Ilday, Serim; Tokel, Onur; Ibrahim, Muhamet; Yavuz, Ozgun; Pavlov, Ihor; Gulseren, Oguz; Ilday, Omer

The detection, observation, and analysis of material phases and atomistic patterns are of great importance for understanding systems exhibiting both equilibrium and far-from-equilibrium dynamics. As such, there is intense research on phase transitions and pattern dynamics in soft matter, statistical and nonlinear physics, and polymer physics. In order to identify phases and nano-patterns, the pair correlation function is commonly used. However, this approach is limited in terms of recognizing competing patterns in dynamic systems, and lacks visualisation capabilities. In order to solve these limitations, we introduce Lindemann histogram quantification as an alternative method to analyse solid, liquid, and gas phases, along with hexagonal, square, and amorphous nano-pattern symmetries. We show that the proposed approach based on Lindemann parameter calculated per particle maps local number densities to material phase or particles pattern. We apply the Lindemann histogram method on dynamical colloidal self-assembly experimental data and identify competing patterns.

Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

NASA Astrophysics Data System (ADS)

Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

2018-04-01

In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

Adaptive image contrast enhancement using generalizations of histogram equalization.

PubMed

Stark, J A

2000-01-01

This paper proposes a scheme for adaptive image-contrast enhancement based on a generalization of histogram equalization (HE). HE is a useful technique for improving image contrast, but its effect is too severe for many purposes. However, dramatically different results can be obtained with relatively minor modifications. A concise description of adaptive HE is set out, and this framework is used in a discussion of past suggestions for variations on HE. A key feature of this formalism is a "cumulation function," which is used to generate a grey level mapping from the local histogram. By choosing alternative forms of cumulation function one can achieve a wide variety of effects. A specific form is proposed. Through the variation of one or two parameters, the resulting process can produce a range of degrees of contrast enhancement, at one extreme leaving the image unchanged, at another yielding full adaptive equalization.

Efficient HIK SVM learning for image classification.

PubMed

Wu, Jianxin

2012-10-01

Histograms are used in almost every aspect of image processing and computer vision, from visual descriptors to image representations. Histogram intersection kernel (HIK) and support vector machine (SVM) classifiers are shown to be very effective in dealing with histograms. This paper presents contributions concerning HIK SVM for image classification. First, we propose intersection coordinate descent (ICD), a deterministic and scalable HIK SVM solver. ICD is much faster than, and has similar accuracies to, general purpose SVM solvers and other fast HIK SVM training methods. We also extend ICD to the efficient training of a broader family of kernels. Second, we show an important empirical observation that ICD is not sensitive to the C parameter in SVM, and we provide some theoretical analyses to explain this observation. ICD achieves high accuracies in many problems, using its default parameters. This is an attractive property for practitioners, because many image processing tasks are too large to choose SVM parameters using cross-validation.

A method for real-time implementation of HOG feature extraction

NASA Astrophysics Data System (ADS)

Luo, Hai-bo; Yu, Xin-rong; Liu, Hong-mei; Ding, Qing-hai

2011-08-01

Histogram of oriented gradient (HOG) is an efficient feature extraction scheme, and HOG descriptors are feature descriptors which is widely used in computer vision and image processing for the purpose of biometrics, target tracking, automatic target detection(ATD) and automatic target recognition(ATR) etc. However, computation of HOG feature extraction is unsuitable for hardware implementation since it includes complicated operations. In this paper, the optimal design method and theory frame for real-time HOG feature extraction based on FPGA were proposed. The main principle is as follows: firstly, the parallel gradient computing unit circuit based on parallel pipeline structure was designed. Secondly, the calculation of arctangent and square root operation was simplified. Finally, a histogram generator based on parallel pipeline structure was designed to calculate the histogram of each sub-region. Experimental results showed that the HOG extraction can be implemented in a pixel period by these computing units.

Multi-stream LSTM-HMM decoding and histogram equalization for noise robust keyword spotting.

PubMed

Wöllmer, Martin; Marchi, Erik; Squartini, Stefano; Schuller, Björn

2011-09-01

Highly spontaneous, conversational, and potentially emotional and noisy speech is known to be a challenge for today's automatic speech recognition (ASR) systems, which highlights the need for advanced algorithms that improve speech features and models. Histogram Equalization is an efficient method to reduce the mismatch between clean and noisy conditions by normalizing all moments of the probability distribution of the feature vector components. In this article, we propose to combine histogram equalization and multi-condition training for robust keyword detection in noisy speech. To better cope with conversational speaking styles, we show how contextual information can be effectively exploited in a multi-stream ASR framework that dynamically models context-sensitive phoneme estimates generated by a long short-term memory neural network. The proposed techniques are evaluated on the SEMAINE database-a corpus containing emotionally colored conversations with a cognitive system for "Sensitive Artificial Listening".

Content-based unconstrained color logo and trademark retrieval with color edge gradient co-occurrence histograms

NASA Astrophysics Data System (ADS)

Phan, Raymond; Androutsos, Dimitrios

2008-01-01

In this paper, we present a logo and trademark retrieval system for unconstrained color image databases that extends the Color Edge Co-occurrence Histogram (CECH) object detection scheme. We introduce more accurate information to the CECH, by virtue of incorporating color edge detection using vector order statistics. This produces a more accurate representation of edges in color images, in comparison to the simple color pixel difference classification of edges as seen in the CECH. Our proposed method is thus reliant on edge gradient information, and as such, we call this the Color Edge Gradient Co-occurrence Histogram (CEGCH). We use this as the main mechanism for our unconstrained color logo and trademark retrieval scheme. Results illustrate that the proposed retrieval system retrieves logos and trademarks with good accuracy, and outperforms the CECH object detection scheme with higher precision and recall.

Correlation of 18F-FDG PET and MRI Apparent Diffusion Coefficient Histogram Metrics with Survival in Diffuse Intrinsic Pontine Glioma: A Report from the Pediatric Brain Tumor Consortium.

PubMed

Zukotynski, Katherine A; Vajapeyam, Sridhar; Fahey, Frederic H; Kocak, Mehmet; Brown, Douglas; Ricci, Kelsey I; Onar-Thomas, Arzu; Fouladi, Maryam; Poussaint, Tina Young

2017-08-01

The purpose of this study was to describe baseline 18 F-FDG PET voxel characteristics in pediatric diffuse intrinsic pontine glioma (DIPG) and to correlate these metrics with baseline MRI apparent diffusion coefficient (ADC) histogram metrics, progression-free survival (PFS), and overall survival. Methods: Baseline brain 18 F-FDG PET and MRI scans were obtained in 33 children from Pediatric Brain Tumor Consortium clinical DIPG trials. 18 F-FDG PET images, postgadolinium MR images, and ADC MR images were registered to baseline fluid attenuation inversion recovery MR images. Three-dimensional regions of interest on fluid attenuation inversion recovery MR images and postgadolinium MR images and 18 F-FDG PET and MR ADC histograms were generated. Metrics evaluated included peak number, skewness, and kurtosis. Correlation between PET and MR ADC histogram metrics was evaluated. PET pixel values within the region of interest for each tumor were plotted against MR ADC values. The association of these imaging markers with survival was described. Results: PET histograms were almost always unimodal (94%, vs. 6% bimodal). None of the PET histogram parameters (skewness or kurtosis) had a significant association with PFS, although a higher PET postgadolinium skewness tended toward a less favorable PFS (hazard ratio, 3.48; 95% confidence interval [CI], 0.75-16.28 [ P = 0.11]). There was a significant association between higher MR ADC postgadolinium skewness and shorter PFS (hazard ratio, 2.56; 95% CI, 1.11-5.91 [ P = 0.028]), and there was the suggestion that this also led to shorter overall survival (hazard ratio, 2.18; 95% CI, 0.95-5.04 [ P = 0.067]). Higher MR ADC postgadolinium kurtosis tended toward shorter PFS (hazard ratio, 1.30; 95% CI, 0.98-1.74 [ P = 0.073]). PET and MR ADC pixel values were negatively correlated using the Pearson correlation coefficient. Further, the level of PET and MR ADC correlation was significantly positively associated with PFS; tumors with higher values of ADC-PET correlation had more favorable PFS (hazard ratio, 0.17; 95% CI, 0.03-0.89 [ P = 0.036]), suggesting that a higher level of negative ADC-PET correlation leads to less favorable PFS. A more significant negative correlation may indicate higher-grade elements within the tumor leading to poorer outcomes. Conclusion: 18 F-FDG PET and MR ADC histogram metrics in pediatric DIPG demonstrate different characteristics with often a negative correlation between PET and MR ADC pixel values. A higher negative correlation is associated with a worse PFS, which may indicate higher-grade elements within the tumor. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

A Virtual Blind Cane Using a Line Laser-Based Vision System and an Inertial Measurement Unit

PubMed Central

Dang, Quoc Khanh; Chee, Youngjoon; Pham, Duy Duong; Suh, Young Soo

2016-01-01

A virtual blind cane system for indoor application, including a camera, a line laser and an inertial measurement unit (IMU), is proposed in this paper. Working as a blind cane, the proposed system helps a blind person find the type of obstacle and the distance to it. The distance from the user to the obstacle is estimated by extracting the laser coordinate points on the obstacle, as well as tracking the system pointing angle. The paper provides a simple method to classify the obstacle’s type by analyzing the laser intersection histogram. Real experimental results are presented to show the validity and accuracy of the proposed system. PMID:26771618

Peak Doctor v 1.0.0 Labview Version

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

Garner, Scott

2014-05-29

PeakDoctor software works interactively with its user to analyze raw gamma-ray spectroscopic data. The goal of the software is to produce a list of energies and areas of all of the peaks in the spectrum, as accurately as possible. It starts by performing an energy calibration, creating a function that describes how energy can be related to channel number. Next, the software determines which channels in the raw histogram are in the Compton continuum and which channels are parts of a peak. Then the software fits the Compton continuum with cubic polynomials. The last step is to fit all ofmore » the peaks with Gaussian functions, thus producing the list.« less

Characteristics of extreme rainfall events in northwestern Peru during the 1982-1983 El Nino period

NASA Technical Reports Server (NTRS)

Goldberg, R. A.; Tisnado, G. M.; Scofield, R. A.

1987-01-01

Histograms and contour maps describing the daily rainfall characteristics of a northwestern Peru area most severely affected by the 1982-1983 El Nino event were prepared from daily rainfall data obtained from 66 stations in this area during the El Nino event, and during the same 8-month intervals for the two years preceding and following the event. These data were analyzed, in conjunction with the anlysis of visible and IR satellite images, for cloud characteristics and structure. The results present a comparison of the rainfall characteristics as a function of elevation, geographic location, and the time of year for the El Nino and non-El Nino periods.

Criticality in Neuronal Networks

NASA Astrophysics Data System (ADS)

Friedman, Nir; Ito, Shinya; Brinkman, Braden A. W.; Shimono, Masanori; Deville, R. E. Lee; Beggs, John M.; Dahmen, Karin A.; Butler, Tom C.

2012-02-01

In recent years, experiments detecting the electrical firing patterns in slices of in vitro brain tissue have been analyzed to suggest the presence of scale invariance and possibly criticality in the brain. Much of the work done however has been limited in two ways: 1) the data collected is from local field potentials that do not represent the firing of individual neurons; 2) the analysis has been primarily limited to histograms. In our work we examine data based on the firing of individual neurons (spike data), and greatly extend the analysis by considering shape collapse and exponents. Our results strongly suggest that the brain operates near a tuned critical point of a highly distinctive universality class.

Dependence of Interfacial Excess on the Threshold Value of the Isoconcentration Surface

NASA Technical Reports Server (NTRS)

Yoon, Kevin E.; Noebe, Ronald D.; Hellman, Olof C.; Seidman, David N.

2004-01-01

The proximity histogram (or proxigram for short) is used for analyzing data collected by a three-dimensional atom probe microscope. The interfacial excess of Re (2.41 +/- 0.68 atoms/sq nm) is calculated by employing a proxigram in a completely geometrically independent way for gamma/gamma' interfaces in Rene N6, a third-generation single-crystal Ni-based superalloy. A possible dependence of interfacial excess on the variation of the threshold value of an isoconcentration surface is investigated using the data collected for Rene N6 alloy. It is demonstrated that the dependence of the interfacial excess value on the threshold value of the isoconcentration surface is weak.

Ultrasound estimates of muscle quality in older adults: reliability and comparison of Photoshop and ImageJ for the grayscale analysis of muscle echogenicity

PubMed Central

Seamon, Bryant A.; Teixeira, Carla; Ismail, Catheeja

2016-01-01

Background. Quantitative diagnostic ultrasound imaging has been proposed as a method of estimating muscle quality using measures of echogenicity. The Rectangular Marquee Tool (RMT) and the Free Hand Tool (FHT) are two types of editing features used in Photoshop and ImageJ for determining a region of interest (ROI) within an ultrasound image. The primary objective of this study is to determine the intrarater and interrater reliability of Photoshop and ImageJ for the estimate of muscle tissue echogenicity in older adults via grayscale histogram analysis. The secondary objective is to compare the mean grayscale values obtained using both the RMT and FHT methods across both image analysis platforms. Methods. This cross-sectional observational study features 18 community-dwelling men (age = 61.5 ± 2.32 years). Longitudinal views of the rectus femoris were captured using B-mode ultrasound. The ROI for each scan was selected by 2 examiners using the RMT and FHT methods from each software program. Their reliability is assessed using intraclass correlation coefficients (ICCs) and the standard error of the measurement (SEM). Measurement agreement for these values is depicted using Bland-Altman plots. A paired t-test is used to determine mean differences in echogenicity expressed as grayscale values using the RMT and FHT methods to select the post-image acquisition ROI. The degree of association among ROI selection methods and image analysis platforms is analyzed using the coefficient of determination (R2). Results. The raters demonstrated excellent intrarater and interrater reliability using the RMT and FHT methods across both platforms (lower bound 95% CI ICC = .97–.99, p < .001). Mean differences between the echogenicity estimates obtained with the RMT and FHT methods was .87 grayscale levels (95% CI [.54–1.21], p < .0001) using data obtained with both programs. The SEM for Photoshop was .97 and 1.05 grayscale levels when using the RMT and FHT ROI selection methods, respectively. Comparatively, the SEM values were .72 and .81 grayscale levels, respectively, when using the RMT and FHT ROI selection methods in ImageJ. Uniform coefficients of determination (R2 = .96–.99, p < .001) indicate strong positive associations among the grayscale histogram analysis measurement conditions independent of the ROI selection methods and imaging platform. Conclusion. Our method for evaluating muscle echogenicity demonstrated a high degree of intrarater and interrater reliability using both the RMT and FHT methods across 2 common image analysis platforms. The minimal measurement error exhibited by the examiners demonstrates that the ROI selection methods used with Photoshop and ImageJ are suitable for the post-acquisition image analysis of tissue echogenicity in older adults. PMID:26925339

Satellite interference analysis and simulation using personal computers

NASA Astrophysics Data System (ADS)

Kantak, Anil

1988-03-01

This report presents the complete analysis and formulas necessary to quantify the interference experienced by a generic satellite communications receiving station due to an interfering satellite. Both satellites, the desired as well as the interfering satellite, are considered to be in elliptical orbits. Formulas are developed for the satellite look angles and the satellite transmit angles generally related to the land mask of the receiving station site for both satellites. Formulas for considering Doppler effect due to the satellite motion as well as the Earth's rotation are developed. The effect of the interfering-satellite signal modulation and the Doppler effect on the power received are considered. The statistical formulation of the interference effect is presented in the form of a histogram of the interference to the desired signal power ratio. Finally, a computer program suitable for microcomputers such as IBM AT is provided with the flowchart, a sample run, results of the run, and the program code.

Satellite Interference Analysis and Simulation Using Personal Computers

NASA Technical Reports Server (NTRS)

Kantak, Anil

1988-01-01

This report presents the complete analysis and formulas necessary to quantify the interference experienced by a generic satellite communications receiving station due to an interfering satellite. Both satellites, the desired as well as the interfering satellite, are considered to be in elliptical orbits. Formulas are developed for the satellite look angles and the satellite transmit angles generally related to the land mask of the receiving station site for both satellites. Formulas for considering Doppler effect due to the satellite motion as well as the Earth's rotation are developed. The effect of the interfering-satellite signal modulation and the Doppler effect on the power received are considered. The statistical formulation of the interference effect is presented in the form of a histogram of the interference to the desired signal power ratio. Finally, a computer program suitable for microcomputers such as IBM AT is provided with the flowchart, a sample run, results of the run, and the program code.

Aperture Photometry Tool

NASA Astrophysics Data System (ADS)

Laher, Russ R.; Gorjian, Varoujan; Rebull, Luisa M.; Masci, Frank J.; Fowler, John W.; Helou, George; Kulkarni, Shrinivas R.; Law, Nicholas M.

2012-07-01

Aperture Photometry Tool (APT) is software for astronomers and students interested in manually exploring the photometric qualities of astronomical images. It is a graphical user interface (GUI) designed to allow the image data associated with aperture photometry calculations for point and extended sources to be visualized and, therefore, more effectively analyzed. The finely tuned layout of the GUI, along with judicious use of color-coding and alerting, is intended to give maximal user utility and convenience. Simply mouse-clicking on a source in the displayed image will instantly draw a circular or elliptical aperture and sky annulus around the source and will compute the source intensity and its uncertainty, along with several commonly used measures of the local sky background and its variability. The results are displayed and can be optionally saved to an aperture-photometry-table file and plotted on graphs in various ways using functions available in the software. APT is geared toward processing sources in a small number of images and is not suitable for bulk processing a large number of images, unlike other aperture photometry packages (e.g., SExtractor). However, APT does have a convenient source-list tool that enables calculations for a large number of detections in a given image. The source-list tool can be run either in automatic mode to generate an aperture photometry table quickly or in manual mode to permit inspection and adjustment of the calculation for each individual detection. APT displays a variety of useful graphs with just the push of a button, including image histogram, x and y aperture slices, source scatter plot, sky scatter plot, sky histogram, radial profile, curve of growth, and aperture-photometry-table scatter plots and histograms. APT has many functions for customizing the calculations, including outlier rejection, pixel “picking” and “zapping,” and a selection of source and sky models. The radial-profile-interpolation source model, which is accessed via the radial-profile-plot panel, allows recovery of source intensity from pixels with missing data and can be especially beneficial in crowded fields.

Location of Rotator Cuff Tear Initiation: A Magnetic Resonance Imaging Study of 191 Shoulders.

PubMed

Jeong, Jeung Yeol; Min, Seul Ki; Park, Keun Min; Park, Yong Bok; Han, Kwang Joon; Yoo, Jae Chul

2018-03-01

Degenerative rotator cuff tears (RCTs) are generally thought to originate at the anterior margin of the supraspinatus tendon. However, a recent ultrasonography study suggested that they might originate more posteriorly than originally thought, perhaps even from the isolated infraspinatus (ISP) tendon, and propagate toward the anterior supraspinatus. Hypothesis/Purpose: It was hypothesized that this finding could be reproduced with magnetic resonance imaging (MRI). The purpose was to determine the most common location of degenerative RCTs by using 3-dimensional multiplanar MRI reconstruction. It was assumed that the location of the partial-thickness tears would identify the area of the initiation of full-thickness tears. Cross-sectional study; Level of evidence, 3. A retrospective analysis was conducted including 245 patients who had RCTs (nearly full- or partial-thickness tears) at the outpatient department between January 2011 and December 2013. RCTs were measured on 3-dimensional multiplanar reconstruction MRI with OsiriX software. The width and distance from the biceps tendon to the anterior margin of the tear were measured on T2-weighted sagittal images. In a spreadsheet, columns of consecutive numbers represented the size of each tear (anteroposterior width) and their locations with respect to the biceps brachii tendon. Data were pooled to graphically represent the width and location of all tears. Frequency histograms of the columns were made to visualize the distribution of tears. The tears were divided into 2 groups based on width (group A, <10 mm; group B, <20 and ≥10 mm) and analyzed for any differences in location related to size. The mean width of all RCTs was 11.9 ± 4.1 mm, and the mean length was 11.1 ± 5.0 mm. Histograms showed the most common location of origin to be 9 to 10 mm posterior to the biceps tendon. The histograms of groups A and B showed similar tear location distributions, indicating that the region approximately 10 mm posterior to the biceps tendon is the most common site of tear initiation. These results demonstrate that degenerative RCTs most commonly originate from approximately 9 to 10 mm posterior to the biceps tendon.

Incremental Prognostic Value of Apparent Diffusion Coefficient Histogram Analysis in Head and Neck Squamous Cell Carcinoma.

PubMed

Li, Xiaoxia; Yuan, Ying; Ren, Jiliang; Shi, Yiqian; Tao, Xiaofeng

2018-03-26

We aimed to investigate the incremental prognostic value of apparent diffusion coefficient (ADC) histogram analysis in patients with head and neck squamous cell carcinoma (HNSCC) and integrate it into a multivariate prognostic model. A retrospective review of magnetic resonance imaging findings was conducted in patients with pathologically confirmed HNSCC between June 2012 and December 2015. For each tumor, six histogram parameters were derived: the 10th, 50th, and 90th percentiles of ADC (ADC 10 , ADC 50 , and ADC 90 ); mean ADC values (ADC mean ); kurtosis; and skewness. The clinical variables included age, sex, smoking status, tumor volume, and tumor node metastasis stage. The association of these histogram and clinical variables with overall survival (OS) was determined. Further validation of the histogram parameters as independent biomarkers was performed using multivariate Cox proportional hazard models combined with clinical variables, which was compared to the clinical model. Models were assessed with C index and receiver operating characteristic curve analyses for the 12- and 36-month OS. Ninety-six patients were eligible for analysis. Median follow-up was 877 days (range, 54-1516 days). A total of 29 patients died during follow-up (30%). Patients with higher ADC values (ADC 10  > 0.958 × 10 -3 mm 2 /s, ADC 50  > 1.089 × 10 -3 mm 2 /s, ADC 90  > 1.152 × 10 -3 mm 2 /s, ADC mean  > 1.047 × 10 -3 mm 2 /s) and lower kurtosis (≤0.967) were significant predictors of poor OS (P < .100 for all). After adjusting for sex and tumor node metastasis stage, the ADC 90 and kurtosis are both significant predictors of OS with hazard ratios = 1.00 (95% confidence interval: 1.001-1.004) and 0.58 (95% confidence interval: 0.37-0.90), respectively. By adding the ADC parameters into the clinical model, the C index and diagnostic accuracies for the 12- and 36-month OS showed significant improvement. ADC histogram analysis has incremental prognostic value in patients with HNSCC and increases the performance of a multivariable prognostic model in addition to clinical variables. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Measuring kinetics of complex single ion channel data using mean-variance histograms.

PubMed

Patlak, J B

1993-07-01

The measurement of single ion channel kinetics is difficult when those channels exhibit subconductance events. When the kinetics are fast, and when the current magnitudes are small, as is the case for Na+, Ca2+, and some K+ channels, these difficulties can lead to serious errors in the estimation of channel kinetics. I present here a method, based on the construction and analysis of mean-variance histograms, that can overcome these problems. A mean-variance histogram is constructed by calculating the mean current and the current variance within a brief "window" (a set of N consecutive data samples) superimposed on the digitized raw channel data. Systematic movement of this window over the data produces large numbers of mean-variance pairs which can be assembled into a two-dimensional histogram. Defined current levels (open, closed, or sublevel) appear in such plots as low variance regions. The total number of events in such low variance regions is estimated by curve fitting and plotted as a function of window width. This function decreases with the same time constants as the original dwell time probability distribution for each of the regions. The method can therefore be used: 1) to present a qualitative summary of the single channel data from which the signal-to-noise ratio, open channel noise, steadiness of the baseline, and number of conductance levels can be quickly determined; 2) to quantify the dwell time distribution in each of the levels exhibited. In this paper I present the analysis of a Na+ channel recording that had a number of complexities. The signal-to-noise ratio was only about 8 for the main open state, open channel noise, and fast flickers to other states were present, as were a substantial number of subconductance states. "Standard" half-amplitude threshold analysis of these data produce open and closed time histograms that were well fitted by the sum of two exponentials, but with apparently erroneous time constants, whereas the mean-variance histogram technique provided a more credible analysis of the open, closed, and subconductance times for the patch. I also show that the method produces accurate results on simulated data in a wide variety of conditions, whereas the half-amplitude method, when applied to complex simulated data shows the same errors as were apparent in the real data. The utility and the limitations of this new method are discussed.

Detecting and Analyzing Corrosion Spots on the Hull of Large Marine Vessels Using Colored 3d LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Aijazi, A. K.; Malaterre, L.; Tazir, M. L.; Trassoudaine, L.; Checchin, P.

2016-06-01

This work presents a new method that automatically detects and analyzes surface defects such as corrosion spots of different shapes and sizes, on large ship hulls. In the proposed method several scans from different positions and viewing angles around the ship are registered together to form a complete 3D point cloud. The R, G, B values associated with each scan, obtained with the help of an integrated camera are converted into HSV space to separate out the illumination invariant color component from the intensity. Using this color component, different surface defects such as corrosion spots of different shapes and sizes are automatically detected, within a selected zone, using two different methods depending upon the level of corrosion/defects. The first method relies on a histogram based distribution whereas the second on adaptive thresholds. The detected corrosion spots are then analyzed and quantified to help better plan and estimate the cost of repair and maintenance. Results are evaluated on real data using different standard evaluation metrics to demonstrate the efficacy as well as the technical strength of the proposed method.

Historical Temporal Shipping (HITS)

DTIC Science & Technology

1978-06-28

Histogram Cells 45 El Figure 4-3 Projection of Area onto Route Perpendicular 45 Figure 4-4 Single Column Cut of Route Envelope 46ii Figure 4-5 Histogram of...Resources, "Super" Bulk Carriers, and Deepwater Port Development." Naval Postgraduate School . June 1974. 8. Gulland, J.A. "The Fish Resources of the Ocean...sailing reports from the various harbour masters. The completeness of the data thus depends in most cases upon the diligence of a single reporting source

Hardware solution for continuous time-resolved burst detection of single molecules in flow

NASA Astrophysics Data System (ADS)

Wahl, Michael; Erdmann, Rainer; Lauritsen, Kristian; Rahn, Hans-Juergen

1998-04-01

Time Correlated Single Photon Counting (TCSPC) is a valuable tool for Single Molecule Detection (SMD). However, existing TCSPC systems did not support continuous data collection and processing as is desirable for applications such as SMD for e.g. DNA-sequencing in a liquid flow. First attempts at using existing instrumentation in this kind of operation mode required additional routing hardware to switch between several memory banks and were not truly continuous. We have designed a hard- and software system to perform continuous real-time TCSPC based upon a modern solid state Time to Digital Converter (TDC). Short dead times of the fully digital TDC design combined with fast Field Programmable Gay Array logic permit a continuous data throughput as high as 3 Mcounts/sec. The histogramming time may be set as short as 100 microsecond(s) . Every histogram or every single fluorescence photon can be real-time tagged at 200 ns resolution in addition to recording its arrival time relative to the excitation pulse. Continuous switching between memory banks permits concurrent histogramming and data read-out. The instrument provides a time resolution of 60 ps and up to 4096 histogram channels. The overall instrument response function in combination with a low cost picosecond diode laser and an inexpensive photomultiplier tube was found to be 180 ps and well sufficient to measure sub-nanosecond fluorescence lifetimes.

Digital image classification with the help of artificial neural network by simple histogram

PubMed Central

Dey, Pranab; Banerjee, Nirmalya; Kaur, Rajwant

2016-01-01

Background: Visual image classification is a great challenge to the cytopathologist in routine day-to-day work. Artificial neural network (ANN) may be helpful in this matter. Aims and Objectives: In this study, we have tried to classify digital images of malignant and benign cells in effusion cytology smear with the help of simple histogram data and ANN. Materials and Methods: A total of 404 digital images consisting of 168 benign cells and 236 malignant cells were selected for this study. The simple histogram data was extracted from these digital images and an ANN was constructed with the help of Neurointelligence software [Alyuda Neurointelligence 2.2 (577), Cupertino, California, USA]. The network architecture was 6-3-1. The images were classified as training set (281), validation set (63), and test set (60). The on-line backpropagation training algorithm was used for this study. Result: A total of 10,000 iterations were done to train the ANN system with the speed of 609.81/s. After the adequate training of this ANN model, the system was able to identify all 34 malignant cell images and 24 out of 26 benign cells. Conclusion: The ANN model can be used for the identification of the individual malignant cells with the help of simple histogram data. This study will be helpful in the future to identify malignant cells in unknown situations. PMID:27279679

Measurement of susceptibility artifacts with histogram-based reference value on magnetic resonance images according to standard ASTM F2119.

PubMed

Heinrich, Andreas; Teichgräber, Ulf K; Güttler, Felix V

2015-12-01

The standard ASTM F2119 describes a test method for measuring the size of a susceptibility artifact based on the example of a passive implant. A pixel in an image is considered to be a part of an image artifact if the intensity is changed by at least 30% in the presence of a test object, compared to a reference image in which the test object is absent (reference value). The aim of this paper is to simplify and accelerate the test method using a histogram-based reference value. Four test objects were scanned parallel and perpendicular to the main magnetic field, and the largest susceptibility artifacts were measured using two methods of reference value determination (reference image-based and histogram-based reference value). The results between both methods were compared using the Mann-Whitney U-test. The difference between both reference values was 42.35 ± 23.66. The difference of artifact size was 0.64 ± 0.69 mm. The artifact sizes of both methods did not show significant differences; the p-value of the Mann-Whitney U-test was between 0.710 and 0.521. A standard-conform method for a rapid, objective, and reproducible evaluation of susceptibility artifacts could be implemented. The result of the histogram-based method does not significantly differ from the ASTM-conform method.

Multi-site Study of Diffusion Metric Variability: Characterizing the Effects of Site, Vendor, Field Strength, and Echo Time using the Histogram Distance

PubMed Central

Helmer, K. G.; Chou, M-C.; Preciado, R. I.; Gimi, B.; Rollins, N. K.; Song, A.; Turner, J.; Mori, S.

2016-01-01

MRI-based multi-site trials now routinely include some form of diffusion-weighted imaging (DWI) in their protocol. These studies can include data originating from scanners built by different vendors, each with their own set of unique protocol restrictions, including restrictions on the number of available gradient directions, whether an externally-generated list of gradient directions can be used, and restrictions on the echo time (TE). One challenge of multi-site studies is to create a common imaging protocol that will result in a reliable and accurate set of diffusion metrics. The present study describes the effect of site, scanner vendor, field strength, and TE on two common metrics: the first moment of the diffusion tensor field (mean diffusivity, MD), and the fractional anisotropy (FA). We have shown in earlier work that ROI metrics and the mean of MD and FA histograms are not sufficiently sensitive for use in site characterization. Here we use the distance between whole brain histograms of FA and MD to investigate within- and between-site effects. We concluded that the variability of DTI metrics due to site, vendor, field strength, and echo time could influence the results in multi-center trials and that histogram distance is sensitive metrics for each of these variables. PMID:27350723

Differential diagnosis of normal pressure hydrocephalus by MRI mean diffusivity histogram analysis.

PubMed

Ivkovic, M; Liu, B; Ahmed, F; Moore, D; Huang, C; Raj, A; Kovanlikaya, I; Heier, L; Relkin, N

2013-01-01

Accurate diagnosis of normal pressure hydrocephalus is challenging because the clinical symptoms and radiographic appearance of NPH often overlap those of other conditions, including age-related neurodegenerative disorders such as Alzheimer and Parkinson diseases. We hypothesized that radiologic differences between NPH and AD/PD can be characterized by a robust and objective MR imaging DTI technique that does not require intersubject image registration or operator-defined regions of interest, thus avoiding many pitfalls common in DTI methods. We collected 3T DTI data from 15 patients with probable NPH and 25 controls with AD, PD, or dementia with Lewy bodies. We developed a parametric model for the shape of intracranial mean diffusivity histograms that separates brain and ventricular components from a third component composed mostly of partial volume voxels. To accurately fit the shape of the third component, we constructed a parametric function named the generalized Voss-Dyke function. We then examined the use of the fitting parameters for the differential diagnosis of NPH from AD, PD, and DLB. Using parameters for the MD histogram shape, we distinguished clinically probable NPH from the 3 other disorders with 86% sensitivity and 96% specificity. The technique yielded 86% sensitivity and 88% specificity when differentiating NPH from AD only. An adequate parametric model for the shape of intracranial MD histograms can distinguish NPH from AD, PD, or DLB with high sensitivity and specificity.

Illusory Late Heavy Bombardments

NASA Astrophysics Data System (ADS)

Boehnke, Patrick; Harrison, T. Mark

2016-09-01

The Late Heavy Bombardment (LHB), a hypothesized impact spike at ˜3.9 Ga, is one of the major scientific concepts to emerge from Apollo-era lunar exploration. A significant portion of the evidence for the existence of the LHB comes from histograms of 40Ar/39Ar “plateau” ages (i.e., regions selected on the basis of apparent isochroneity). However, due to lunar magmatism and overprinting from subsequent impact events, virtually all Apollo-era samples show evidence for 40Ar/39Ar age spectrum disturbances, leaving open the possibility that partial 40Ar* resetting could bias interpretation of bombardment histories due to plateaus yielding misleadingly young ages. We examine this possibility through a physical model of 40Ar* diffusion in Apollo samples and test the uniqueness of the impact histories obtained by inverting plateau age histograms. Our results show that plateau histograms tend to yield age peaks, even in those cases where the input impact curve did not contain such a spike, in part due to the episodic nature of lunar crust or parent body formation. Restated, monotonically declining impact histories yield apparent age peaks that could be misinterpreted as LHB-type events. We further conclude that the assignment of apparent 40Ar/39Ar plateau ages bears an undesirably high degree of subjectivity. When compounded by inappropriate interpretations of histograms constructed from plateau ages, interpretation of apparent, but illusory, impact spikes is likely.

Illusory Late Heavy Bombardments

PubMed Central

Boehnke, Patrick; Harrison, T. Mark

2016-01-01

The Late Heavy Bombardment (LHB), a hypothesized impact spike at ∼3.9 Ga, is one of the major scientific concepts to emerge from Apollo-era lunar exploration. A significant portion of the evidence for the existence of the LHB comes from histograms of 40Ar/39Ar “plateau” ages (i.e., regions selected on the basis of apparent isochroneity). However, due to lunar magmatism and overprinting from subsequent impact events, virtually all Apollo-era samples show evidence for 40Ar/39Ar age spectrum disturbances, leaving open the possibility that partial 40Ar* resetting could bias interpretation of bombardment histories due to plateaus yielding misleadingly young ages. We examine this possibility through a physical model of 40Ar* diffusion in Apollo samples and test the uniqueness of the impact histories obtained by inverting plateau age histograms. Our results show that plateau histograms tend to yield age peaks, even in those cases where the input impact curve did not contain such a spike, in part due to the episodic nature of lunar crust or parent body formation. Restated, monotonically declining impact histories yield apparent age peaks that could be misinterpreted as LHB-type events. We further conclude that the assignment of apparent 40Ar/39Ar plateau ages bears an undesirably high degree of subjectivity. When compounded by inappropriate interpretations of histograms constructed from plateau ages, interpretation of apparent, but illusory, impact spikes is likely. PMID:27621460

Kinematics of Hα Emitting Stars in Andromeda

NASA Astrophysics Data System (ADS)

Ilango, Megha; Ilango, Anita; Damon, Gabriel; Prichard, Laura; Guhathakurta, Puragra; PHAT Collaboration; SPLASH Collaboration

2017-01-01

Studying emission line stars helps improve our understanding of stellar evolution, types of stars, and their environments. In this study, we analyzed stars exhibiting Hα emission (Hα stars) in the Andromeda Galaxy. We used a combination of spectroscopic and photometric diagnostic methods to remove a population of foreground Milky Way (MW) star contaminants from our data set. The Hα stars were selected from a sample of 5295 spectra from the Spectroscopic and Photometric Landscape of Andromeda’s Stellar Halo (SPLASH) survey and accompanying photometric data from the Panchromatic Hubble Andromeda Treasury (PHAT) survey. Velocities of two classes of Hα stars, main sequence (MS) stars and asymptotic giant branch (AGB) stars, were analyzed through a novel Age-Velocity Difference Correlation (AVDC) method, which utilizes line-of-sight velocity differences (LOSVDs) in order to estimate the age of a rare stellar population. Histograms, weighted means, and weighted standard deviations of the LOSVDs were used to conclude that MS stars are more kinematically coherent than AGB stars, and that Hα stars are kinematically comparable and thus close in age to their non-Hα counterparts. With these results, it can definitively be inferred that mass loss is important in two stages of stellar evolution: massive MS and intermediate mass AGB. We hypothesized that this mass loss could either occur as a normal part of MS and AGB evolution, or that it could be emitted by only a subpopulation of MS and AGB stars throughout their life cycle. Our use of the novel AVDC method sets a precedent for the use of similar methods in predicting the ages of rare stellar subgroups.This research was supported by NASA and the National Science Foundation. Most of this work was carried out by high school students working under the auspices of the Science Internship Program at UC Santa Cruz.

Moderated histogram equalization, an automatic means of enhancing the contrast in digital light micrographs reversibly.

PubMed

Entwistle, A

2004-06-01

A means for improving the contrast in the images produced from digital light micrographs is described that requires no intervention by the experimenter: zero-order, scaling, tonally independent, moderated histogram equalization. It is based upon histogram equalization, which often results in digital light micrographs that contain regions that appear to be saturated, negatively biased or very grainy. Here a non-decreasing monotonic function is introduced into the process, which moderates the changes in contrast that are generated. This method is highly effective for all three of the main types of contrast found in digital light micrography: bright objects viewed against a dark background, e.g. fluorescence and dark-ground or dark-field image data sets; bright and dark objects sets against a grey background, e.g. image data sets collected with phase or Nomarski differential interference contrast optics; and darker objects set against a light background, e.g. views of absorbing specimens. Moreover, it is demonstrated that there is a single fixed moderating function, whose actions are independent of the number of elements of image data, which works well with all types of digital light micrographs, including multimodal or multidimensional image data sets. The use of this fixed function is very robust as the appearance of the final image is not altered discernibly when it is applied repeatedly to an image data set. Consequently, moderated histogram equalization can be applied to digital light micrographs as a push-button solution, thereby eliminating biases that those undertaking the processing might have introduced during manual processing. Finally, moderated histogram equalization yields a mapping function and so, through the use of look-up tables, indexes or palettes, the information present in the original data file can be preserved while an image with the improved contrast is displayed on the monitor screen.

SU-G-BRC-08: Evaluation of Dose Mass Histogram as a More Representative Dose Description Method Than Dose Volume Histogram in Lung Cancer Patients

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

Liu, J; Eldib, A; Ma, C

2016-06-15

Purpose: Dose-volume-histogram (DVH) is widely used for plan evaluation in radiation treatment. The concept of dose-mass-histogram (DMH) is expected to provide a more representative description as it accounts for heterogeneity in tissue density. This study is intended to assess the difference between DVH and DMH for evaluating treatment planning quality. Methods: 12 lung cancer treatment plans were exported from the treatment planning system. DVHs for the planning target volume (PTV), the normal lung and other structures of interest were calculated. DMHs were calculated in a similar way as DVHs expect that the voxel density converted from the CT number wasmore » used in tallying the dose histogram bins. The equivalent uniform dose (EUD) was calculated based on voxel volume and mass, respectively. The normal tissue complication probability (NTCP) in relation to the EUD was calculated for the normal lung to provide quantitative comparison of DVHs and DMHs for evaluating the radiobiological effect. Results: Large differences were observed between DVHs and DMHs for lungs and PTVs. For PTVs with dense tumor cores, DMHs are higher than DVHs due to larger mass weighing in the high dose conformal core regions. For the normal lungs, DMHs can either be higher or lower than DVHs depending on the target location within the lung. When the target is close to the lower lung, DMHs show higher values than DVHs because the lower lung has higher density than the central portion or the upper lung. DMHs are lower than DVHs for targets in the upper lung. The calculated NTCPs showed a large range of difference between DVHs and DMHs. Conclusion: The heterogeneity of lung can be well considered using DMH for evaluating target coverage and normal lung pneumonitis. Further studies are warranted to quantify the benefits of DMH over DVH for plan quality evaluation.« less

Quantitative Image Quality and Histogram-Based Evaluations of an Iterative Reconstruction Algorithm at Low-to-Ultralow Radiation Dose Levels: A Phantom Study in Chest CT

PubMed Central

Lee, Ki Baek

2018-01-01

Objective To describe the quantitative image quality and histogram-based evaluation of an iterative reconstruction (IR) algorithm in chest computed tomography (CT) scans at low-to-ultralow CT radiation dose levels. Materials and Methods In an adult anthropomorphic phantom, chest CT scans were performed with 128-section dual-source CT at 70, 80, 100, 120, and 140 kVp, and the reference (3.4 mGy in volume CT Dose Index [CTDIvol]), 30%-, 60%-, and 90%-reduced radiation dose levels (2.4, 1.4, and 0.3 mGy). The CT images were reconstructed by using filtered back projection (FBP) algorithms and IR algorithm with strengths 1, 3, and 5. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were statistically compared between different dose levels, tube voltages, and reconstruction algorithms. Moreover, histograms of subtraction images before and after standardization in x- and y-axes were visually compared. Results Compared with FBP images, IR images with strengths 1, 3, and 5 demonstrated image noise reduction up to 49.1%, SNR increase up to 100.7%, and CNR increase up to 67.3%. Noteworthy image quality degradations on IR images including a 184.9% increase in image noise, 63.0% decrease in SNR, and 51.3% decrease in CNR, and were shown between 60% and 90% reduced levels of radiation dose (p < 0.0001). Subtraction histograms between FBP and IR images showed progressively increased dispersion with increased IR strength and increased dose reduction. After standardization, the histograms appeared deviated and ragged between FBP images and IR images with strength 3 or 5, but almost normally-distributed between FBP images and IR images with strength 1. Conclusion The IR algorithm may be used to save radiation doses without substantial image quality degradation in chest CT scanning of the adult anthropomorphic phantom, down to approximately 1.4 mGy in CTDIvol (60% reduced dose). PMID:29354008

The ultraviolet detection component based on Te-Cs image intensifier

NASA Astrophysics Data System (ADS)

Qian, Yunsheng; Zhou, Xiaoyu; Wu, Yujing; Wang, Yan; Xu, Hua

2017-05-01

Ultraviolet detection technology has been widely focused and adopted in the fields of ultraviolet warning and corona detection for its significant value and practical meaning. The component structure of ultraviolet ICMOS, imaging driving and the photon counting algorithm are studied in this paper. Firstly, the one-inch and wide dynamic range CMOS chip with the coupling optical fiber panel is coupled to the ultraviolet image intensifier. The photocathode material in ultraviolet image intensifier is Te-Cs, which contributes to the solar blind characteristic, and the dual micro-channel plates (MCP) structure ensures the sufficient gain to achieve the single photon counting. Then, in consideration of the ultraviolet detection demand, the drive circuit of the CMOS chip is designed and the corresponding program based on Verilog language is written. According to the characteristics of ultraviolet imaging, the histogram equalization method is applied to enhance the ultraviolet image and the connected components labeling way is utilized for the ultraviolet single photon counting. Moreover, one visible light video channel is reserved in the ultraviolet ICOMS camera, which can be used for the fusion of ultraviolet and visible images. Based upon the module, the ultraviolet optical lens and the deep cut-off solar blind filter are adopted to construct the ultraviolet detector. At last, the detection experiment of the single photon signal is carried out, and the test results are given and analyzed.

Verification of Dose Distribution in Carbon Ion Radiation Therapy for Stage I Lung Cancer

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

Irie, Daisuke; Saitoh, Jun-ichi, E-mail: junsaito@gunma-u.ac.jp; Shirai, Katsuyuki

Purpose: To evaluate robustness of dose distribution of carbon-ion radiation therapy (C-ion RT) in non-small cell lung cancer (NSCLC) and to identify factors affecting the dose distribution by simulated dose distribution. Methods and Materials: Eighty irradiation fields for delivery of C-ion RT were analyzed in 20 patients with stage I NSCLC. Computed tomography images were obtained twice before treatment initiation. Simulated dose distribution was reconstructed on computed tomography for confirmation under the same settings as actual treatment with respiratory gating and bony structure matching. Dose-volume histogram parameters, such as %D95 (percentage of D95 relative to the prescribed dose), were calculated.more » Patients with any field for which the %D95 of gross tumor volume (GTV) was below 90% were classified as unacceptable for treatment, and the optimal target margin for such cases was examined. Results: Five patients with a total of 8 fields (10% of total number of fields analyzed) were classified as unacceptable according to %D95 of GTV, although most patients showed no remarkable change in the dose-volume histogram parameters. Receiver operating characteristic curve analysis showed that tumor displacement and change in water-equivalent pathlength were significant predictive factors of unacceptable cases (P<.001 and P=.002, respectively). The main cause of degradation of the dose distribution was tumor displacement in 7 of the 8 unacceptable fields. A 6-mm planning target volume margin ensured a GTV %D95 of >90%, except in 1 extremely unacceptable field. Conclusions: According to this simulation analysis of C-ion RT for stage I NSCLC, a few fields were reported as unacceptable and required resetting of body position and reconfirmation. In addition, tumor displacement and change in water-equivalent pathlength (bone shift and/or chest wall thickness) were identified as factors influencing the robustness of dose distribution. Such uncertainties should be regarded in planning.« less

Survival Associations Using Perfusion and Diffusion Magnetic Resonance Imaging in Patients With Histologic and Genetic Defined Diffuse Glioma World Health Organization Grades II and III.

PubMed

Latysheva, Anna; Eeg Emblem, Kyrre; Server, Andrés; Brandal, Petter; Meling, Torstein R; Pahnke, Jens; Hald, John K

2018-06-12

According to the new World Health Organization 2016 classification for tumors of the central nervous system, 1p/19q codeletion defines the genetic hallmark that differentiates oligodendrogliomas from diffuse astrocytomas. The aim of our study was to evaluate whether relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) histogram analysis can stratify survival in adult patients with genetic defined diffuse glioma grades II and III. Sixty-seven patients with untreated diffuse gliomas World Health Organization grades II and III and known 1p/19q codeletion status were included retrospectively and analyzed using ADC and rCBV maps based on whole-tumor volume histograms. Overall survival and progression-free survival (PFS) were analyzed by using Kaplan-Meier and Cox survival analyses adjusted for known survival predictors. Significant longer PFS was associated with homogeneous rCBV distribution-higher rCBVpeak (median, 37 vs 26 months; hazard ratio [HR], 3.2; P = 0.02) in patients with astrocytomas, and heterogeneous rCBV distribution-lower rCBVpeak (median, 46 vs 37 months; HR, 5.3; P < 0.001) and higher rCBVmean (median, 44 vs 39 months; HR, 7.9; P = 0.003) in patients with oligodendrogliomas. Apparent diffusion coefficient parameters (ADCpeak, ADCmean) did not stratify PFS and overall survival. Tumors with heterogeneous perfusion signatures and high average values were associated with longer PFS in patients with oligodendrogliomas. On the contrary, heterogeneous perfusion distribution was associated with poor outcome in patients with diffuse astrocytomas.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

Cross-platform validation and analysis environment for particle physics

NASA Astrophysics Data System (ADS)

Chekanov, S. V.; Pogrebnyak, I.; Wilbern, D.

2017-11-01

A multi-platform validation and analysis framework for public Monte Carlo simulation for high-energy particle collisions is discussed. The front-end of this framework uses the Python programming language, while the back-end is written in Java, which provides a multi-platform environment that can be run from a web browser and can easily be deployed at the grid sites. The analysis package includes all major software tools used in high-energy physics, such as Lorentz vectors, jet algorithms, histogram packages, graphic canvases, and tools for providing data access. This multi-platform software suite, designed to minimize OS-specific maintenance and deployment time, is used for online validation of Monte Carlo event samples through a web interface.

Improving Sector Hash Carving with Rule-Based and Entropy-Based Non-Probative Block Filters

DTIC Science & Technology

2015-03-01

0x20 exceeds the histogram rule’s threshold of 256 instances of a single 4-byte value. The 0x20 bytes are part of an Extensible Metadata Platform (XMP...block consists of data separated by NULL bytes of padding. The histogram rule is triggered for the block because the block contains more than 256 4...sdash can reduce the rate of false positive matches. After characteristic features have been selected, the features are hashed using SHA -1, which creates

Intensity Modulated Radiation Treatment of Prostate Cancer Guided by High Field MR Spectroscopic Imaging

DTIC Science & Technology

2006-05-01

d). (e) In the histogram analysis eld units are observed initially for voxels located on the d to 250 Hounsfield units.ses (a) el the tration...CT10, CT20, and CT30. Histogram ximum difference of 250 Hounsfield units . Only 0.01% d units.d imag ts a mand finite-element model. The fluid flow...cause Hounsfield unit calibration problems. While this does not seem to influence the image registration, the use of CBCT for dose calculation should

Digital enhancement of computerized axial tomograms

NASA Technical Reports Server (NTRS)

Roberts, E., Jr.

1978-01-01

A systematic evaluation was conducted of certain digital image enhancement techniques performed in image space. Three types of images were used, computer generated phantoms, tomograms of a synthetic phantom, and axial tomograms of human anatomy containing images of lesions, artificially introduced into the tomograms. Several types of smoothing, sharpening, and histogram modification were explored. It was concluded that the most useful enhancement techniques are a selective smoothing of singular picture elements, combined with contrast manipulation. The most useful tool in applying these techniques is the gray-scale histogram.

optBINS: Optimal Binning for histograms

NASA Astrophysics Data System (ADS)

Knuth, Kevin H.

2018-03-01

optBINS (optimal binning) determines the optimal number of bins in a uniform bin-width histogram by deriving the posterior probability for the number of bins in a piecewise-constant density model after assigning a multinomial likelihood and a non-informative prior. The maximum of the posterior probability occurs at a point where the prior probability and the the joint likelihood are balanced. The interplay between these opposing factors effectively implements Occam's razor by selecting the most simple model that best describes the data.

WASP (Write a Scientific Paper) using Excel - 4: Histograms.

PubMed

Grech, Victor

2018-02-01

Plotting data into graphs is a crucial step in data analysis as part of an initial descriptive statistics exercise since it gives the researcher an overview of the shape and nature of the data. Outlier values may also be identified, and these may be incorrect data, or true and important outliers. This paper explains how to access Microsoft Excel's Analysis Toolpak and provides some pointers for the utilisation of the histogram tool within the Toolpak. Copyright © 2018. Published by Elsevier B.V.

Modulation Based on Probability Density Functions

NASA Technical Reports Server (NTRS)

Williams, Glenn L.

2009-01-01

A proposed method of modulating a sinusoidal carrier signal to convey digital information involves the use of histograms representing probability density functions (PDFs) that characterize samples of the signal waveform. The method is based partly on the observation that when a waveform is sampled (whether by analog or digital means) over a time interval at least as long as one half cycle of the waveform, the samples can be sorted by frequency of occurrence, thereby constructing a histogram representing a PDF of the waveform during that time interval.

Flood Detection/Monitoring Using Adjustable Histogram Equalization Technique

PubMed Central

Riaz, Muhammad Mohsin; Ghafoor, Abdul

2014-01-01

Flood monitoring technique using adjustable histogram equalization is proposed. The technique overcomes the limitations (overenhancement, artifacts, and unnatural look) of existing technique by adjusting the contrast of images. The proposed technique takes pre- and postimages and applies different processing steps for generating flood map without user interaction. The resultant flood maps can be used for flood monitoring and detection. Simulation results show that the proposed technique provides better output quality compared to the state of the art existing technique. PMID:24558332

Quantitative Ultrasound Using Texture Analysis of Myofascial Pain Syndrome in the Trapezius.

PubMed

Kumbhare, Dinesh A; Ahmed, Sara; Behr, Michael G; Noseworthy, Michael D

2018-01-01

Objective-The objective of this study is to assess the discriminative ability of textural analyses to assist in the differentiation of the myofascial trigger point (MTrP) region from normal regions of skeletal muscle. Also, to measure the ability to reliably differentiate between three clinically relevant groups: healthy asymptomatic, latent MTrPs, and active MTrP. Methods-18 and 19 patients were identified with having active and latent MTrPs in the trapezius muscle, respectively. We included 24 healthy volunteers. Images were obtained by research personnel, who were blinded with respect to the clinical status of the study participant. Histograms provided first-order parameters associated with image grayscale. Haralick, Galloway, and histogram-related features were used in texture analysis. Blob analysis was conducted on the regions of interest (ROIs). Principal component analysis (PCA) was performed followed by multivariate analysis of variance (MANOVA) to determine the statistical significance of the features. Results-92 texture features were analyzed for factorability using Bartlett's test of sphericity, which was significant. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.94. PCA demonstrated rotated eigenvalues of the first eight components (each comprised of multiple texture features) explained 94.92% of the cumulative variance in the ultrasound image characteristics. The 24 features identified by PCA were included in the MANOVA as dependent variables, and the presence of a latent or active MTrP or healthy muscle were independent variables. Conclusion-Texture analysis techniques can discriminate between the three clinically relevant groups.

Equivalent uniform dose concept evaluated by theoretical dose volume histograms for thoracic irradiation.

PubMed

Dumas, J L; Lorchel, F; Perrot, Y; Aletti, P; Noel, A; Wolf, D; Courvoisier, P; Bosset, J F

2007-03-01

The goal of our study was to quantify the limits of the EUD models for use in score functions in inverse planning software, and for clinical application. We focused on oesophagus cancer irradiation. Our evaluation was based on theoretical dose volume histograms (DVH), and we analyzed them using volumetric and linear quadratic EUD models, average and maximum dose concepts, the linear quadratic model and the differential area between each DVH. We evaluated our models using theoretical and more complex DVHs for the above regions of interest. We studied three types of DVH for the target volume: the first followed the ICRU dose homogeneity recommendations; the second was built out of the first requirements and the same average dose was built in for all cases; the third was truncated by a small dose hole. We also built theoretical DVHs for the organs at risk, in order to evaluate the limits of, and the ways to use both EUD(1) and EUD/LQ models, comparing them to the traditional ways of scoring a treatment plan. For each volume of interest we built theoretical treatment plans with differences in the fractionation. We concluded that both volumetric and linear quadratic EUDs should be used. Volumetric EUD(1) takes into account neither hot-cold spot compensation nor the differences in fractionation, but it is more sensitive to the increase of the irradiated volume. With linear quadratic EUD/LQ, a volumetric analysis of fractionation variation effort can be performed.

Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques.

PubMed

Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh

2016-12-01

Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications.

Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques

PubMed Central

Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh

2016-01-01

Background: Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. Methods: In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. Results: With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Conclusion: Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications. PMID:28077898

GPU accelerated population annealing algorithm

NASA Astrophysics Data System (ADS)

Barash, Lev Yu.; Weigel, Martin; Borovský, Michal; Janke, Wolfhard; Shchur, Lev N.

2017-11-01

Population annealing is a promising recent approach for Monte Carlo simulations in statistical physics, in particular for the simulation of systems with complex free-energy landscapes. It is a hybrid method, combining importance sampling through Markov chains with elements of sequential Monte Carlo in the form of population control. While it appears to provide algorithmic capabilities for the simulation of such systems that are roughly comparable to those of more established approaches such as parallel tempering, it is intrinsically much more suitable for massively parallel computing. Here, we tap into this structural advantage and present a highly optimized implementation of the population annealing algorithm on GPUs that promises speed-ups of several orders of magnitude as compared to a serial implementation on CPUs. While the sample code is for simulations of the 2D ferromagnetic Ising model, it should be easily adapted for simulations of other spin models, including disordered systems. Our code includes implementations of some advanced algorithmic features that have only recently been suggested, namely the automatic adaptation of temperature steps and a multi-histogram analysis of the data at different temperatures. Program Files doi:http://dx.doi.org/10.17632/sgzt4b7b3m.1 Licensing provisions: Creative Commons Attribution license (CC BY 4.0) Programming language: C, CUDA External routines/libraries: NVIDIA CUDA Toolkit 6.5 or newer Nature of problem: The program calculates the internal energy, specific heat, several magnetization moments, entropy and free energy of the 2D Ising model on square lattices of edge length L with periodic boundary conditions as a function of inverse temperature β. Solution method: The code uses population annealing, a hybrid method combining Markov chain updates with population control. The code is implemented for NVIDIA GPUs using the CUDA language and employs advanced techniques such as multi-spin coding, adaptive temperature steps and multi-histogram reweighting. Additional comments: Code repository at https://github.com/LevBarash/PAising. The system size and size of the population of replicas are limited depending on the memory of the GPU device used. For the default parameter values used in the sample programs, L = 64, θ = 100, β0 = 0, βf = 1, Δβ = 0 . 005, R = 20 000, a typical run time on an NVIDIA Tesla K80 GPU is 151 seconds for the single spin coded (SSC) and 17 seconds for the multi-spin coded (MSC) program (see Section 2 for a description of these parameters).

A flower image retrieval method based on ROI feature.

PubMed

Hong, An-Xiang; Chen, Gang; Li, Jun-Li; Chi, Zhe-Ru; Zhang, Dan

2004-07-01

Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).

High capacity reversible watermarking for audio by histogram shifting and predicted error expansion.

PubMed

Wang, Fei; Xie, Zhaoxin; Chen, Zuo

2014-01-01

Being reversible, the watermarking information embedded in audio signals can be extracted while the original audio data can achieve lossless recovery. Currently, the few reversible audio watermarking algorithms are confronted with following problems: relatively low SNR (signal-to-noise) of embedded audio; a large amount of auxiliary embedded location information; and the absence of accurate capacity control capability. In this paper, we present a novel reversible audio watermarking scheme based on improved prediction error expansion and histogram shifting. First, we use differential evolution algorithm to optimize prediction coefficients and then apply prediction error expansion to output stego data. Second, in order to reduce location map bits length, we introduced histogram shifting scheme. Meanwhile, the prediction error modification threshold according to a given embedding capacity can be computed by our proposed scheme. Experiments show that this algorithm improves the SNR of embedded audio signals and embedding capacity, drastically reduces location map bits length, and enhances capacity control capability.

Spatial detection of tv channel logos as outliers from the content

NASA Astrophysics Data System (ADS)

Ekin, Ahmet; Braspenning, Ralph

2006-01-01

This paper proposes a purely image-based TV channel logo detection algorithm that can detect logos independently from their motion and transparency features. The proposed algorithm can robustly detect any type of logos, such as transparent and animated, without requiring any temporal constraints whereas known methods have to wait for the occurrence of large motion in the scene and assume stationary logos. The algorithm models logo pixels as outliers from the actual scene content that is represented by multiple 3-D histograms in the YC BC R space. We use four scene histograms corresponding to each of the four corners because the content characteristics change from one image corner to another. A further novelty of the proposed algorithm is that we define image corners and the areas where we compute the scene histograms by a cinematic technique called Golden Section Rule that is used by professionals. The robustness of the proposed algorithm is demonstrated over a dataset of representative TV content.

Object-based change detection method using refined Markov random field

NASA Astrophysics Data System (ADS)

Peng, Daifeng; Zhang, Yongjun

2017-01-01

In order to fully consider the local spatial constraints between neighboring objects in object-based change detection (OBCD), an OBCD approach is presented by introducing a refined Markov random field (MRF). First, two periods of images are stacked and segmented to produce image objects. Second, object spectral and textual histogram features are extracted and G-statistic is implemented to measure the distance among different histogram distributions. Meanwhile, object heterogeneity is calculated by combining spectral and textual histogram distance using adaptive weight. Third, an expectation-maximization algorithm is applied for determining the change category of each object and the initial change map is then generated. Finally, a refined change map is produced by employing the proposed refined object-based MRF method. Three experiments were conducted and compared with some state-of-the-art unsupervised OBCD methods to evaluate the effectiveness of the proposed method. Experimental results demonstrate that the proposed method obtains the highest accuracy among the methods used in this paper, which confirms its validness and effectiveness in OBCD.

Exploring gravitational lensing model variations in the Frontier Fields galaxy clusters

NASA Astrophysics Data System (ADS)

Harris James, Nicholas John; Raney, Catie; Brennan, Sean; Keeton, Charles

2018-01-01

Multiple groups have been working on modeling the mass distributions of the six lensing galaxy clusters in the Hubble Space Telescope Frontier Fields data set. The magnification maps produced from these mass models will be important for the future study of the lensed background galaxies, but there exists significant variation in the different groups’ models and magnification maps. We explore the use of two-dimensional histograms as a tool for visualizing these magnification map variations. Using a number of simple, one- or two-halo singular isothermal sphere models, we explore the features that are produced in 2D histogram model comparisons when parameters such as halo mass, ellipticity, and location are allowed to vary. Our analysis demonstrates the potential of 2D histograms as a means of observing the full range of differences between the Frontier Fields groups’ models.This work has been supported by funding from National Science Foundation grants PHY-1560077 and AST-1211385, and from the Space Telescope Science Institute.

An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization

NASA Astrophysics Data System (ADS)

Li, Shuo; Jin, Weiqi; Li, Li; Li, Yiyang

2018-05-01

Infrared thermal images can reflect the thermal-radiation distribution of a particular scene. However, the contrast of the infrared images is usually low. Hence, it is generally necessary to enhance the contrast of infrared images in advance to facilitate subsequent recognition and analysis. Based on the adaptive double plateaus histogram equalization, this paper presents an improved contrast enhancement algorithm for infrared thermal images. In the proposed algorithm, the normalized coefficient of variation of the histogram, which characterizes the level of contrast enhancement, is introduced as feedback information to adjust the upper and lower plateau thresholds. The experiments on actual infrared images show that compared to the three typical contrast-enhancement algorithms, the proposed algorithm has better scene adaptability and yields better contrast-enhancement results for infrared images with more dark areas or a higher dynamic range. Hence, it has high application value in contrast enhancement, dynamic range compression, and digital detail enhancement for infrared thermal images.

Color image enhancement based on particle swarm optimization with Gaussian mixture

NASA Astrophysics Data System (ADS)

Kattakkalil Subhashdas, Shibudas; Choi, Bong-Seok; Yoo, Ji-Hoon; Ha, Yeong-Ho

2015-01-01

This paper proposes a Gaussian mixture based image enhancement method which uses particle swarm optimization (PSO) to have an edge over other contemporary methods. The proposed method uses the guassian mixture model to model the lightness histogram of the input image in CIEL*a*b* space. The intersection points of the guassian components in the model are used to partition the lightness histogram. . The enhanced lightness image is generated by transforming the lightness value in each interval to appropriate output interval according to the transformation function that depends on PSO optimized parameters, weight and standard deviation of Gaussian component and cumulative distribution of the input histogram interval. In addition, chroma compensation is applied to the resulting image to reduce washout appearance. Experimental results show that the proposed method produces a better enhanced image compared to the traditional methods. Moreover, the enhanced image is free from several side effects such as washout appearance, information loss and gradation artifacts.

Decoding brain cancer dynamics: a quantitative histogram-based approach using temporal MRI

NASA Astrophysics Data System (ADS)

Zhou, Mu; Hall, Lawrence O.; Goldgof, Dmitry B.; Russo, Robin; Gillies, Robert J.; Gatenby, Robert A.

2015-03-01

Brain tumor heterogeneity remains a challenge for probing brain cancer evolutionary dynamics. In light of evolution, it is a priority to inspect the cancer system from a time-domain perspective since it explicitly tracks the dynamics of cancer variations. In this paper, we study the problem of exploring brain tumor heterogeneity from temporal clinical magnetic resonance imaging (MRI) data. Our goal is to discover evidence-based knowledge from such temporal imaging data, where multiple clinical MRI scans from Glioblastoma multiforme (GBM) patients are generated during therapy. In particular, we propose a quantitative histogram-based approach that builds a prediction model to measure the difference in histograms obtained from pre- and post-treatment. The study could significantly assist radiologists by providing a metric to identify distinctive patterns within each tumor, which is crucial for the goal of providing patient-specific treatments. We examine the proposed approach for a practical application - clinical survival group prediction. Experimental results show that our approach achieved 90.91% accuracy.

Random walk numerical simulation for hopping transport at finite carrier concentrations: diffusion coefficient and transport energy concept.

PubMed

Gonzalez-Vazquez, J P; Anta, Juan A; Bisquert, Juan

2009-11-28

The random walk numerical simulation (RWNS) method is used to compute diffusion coefficients for hopping transport in a fully disordered medium at finite carrier concentrations. We use Miller-Abrahams jumping rates and an exponential distribution of energies to compute the hopping times in the random walk simulation. The computed diffusion coefficient shows an exponential dependence with respect to Fermi-level and Arrhenius behavior with respect to temperature. This result indicates that there is a well-defined transport level implicit to the system dynamics. To establish the origin of this transport level we construct histograms to monitor the energies of the most visited sites. In addition, we construct "corrected" histograms where backward moves are removed. Since these moves do not contribute to transport, these histograms provide a better estimation of the effective transport level energy. The analysis of this concept in connection with the Fermi-level dependence of the diffusion coefficient and the regime of interest for the functioning of dye-sensitised solar cells is thoroughly discussed.

A novel method for the evaluation of uncertainty in dose-volume histogram computation.

PubMed

Henríquez, Francisco Cutanda; Castrillón, Silvia Vargas

2008-03-15

Dose-volume histograms (DVHs) are a useful tool in state-of-the-art radiotherapy treatment planning, and it is essential to recognize their limitations. Even after a specific dose-calculation model is optimized, dose distributions computed by using treatment-planning systems are affected by several sources of uncertainty, such as algorithm limitations, measurement uncertainty in the data used to model the beam, and residual differences between measured and computed dose. This report presents a novel method to take them into account. To take into account the effect of associated uncertainties, a probabilistic approach using a new kind of histogram, a dose-expected volume histogram, is introduced. The expected value of the volume in the region of interest receiving an absorbed dose equal to or greater than a certain value is found by using the probability distribution of the dose at each point. A rectangular probability distribution is assumed for this point dose, and a formulation that accounts for uncertainties associated with point dose is presented for practical computations. This method is applied to a set of DVHs for different regions of interest, including 6 brain patients, 8 lung patients, 8 pelvis patients, and 6 prostate patients planned for intensity-modulated radiation therapy. Results show a greater effect on planning target volume coverage than in organs at risk. In cases of steep DVH gradients, such as planning target volumes, this new method shows the largest differences with the corresponding DVH; thus, the effect of the uncertainty is larger.

Three-Dimensional Object Recognition and Registration for Robotic Grasping Systems Using a Modified Viewpoint Feature Histogram

PubMed Central

Chen, Chin-Sheng; Chen, Po-Chun; Hsu, Chih-Ming

2016-01-01

This paper presents a novel 3D feature descriptor for object recognition and to identify poses when there are six-degrees-of-freedom for mobile manipulation and grasping applications. Firstly, a Microsoft Kinect sensor is used to capture 3D point cloud data. A viewpoint feature histogram (VFH) descriptor for the 3D point cloud data then encodes the geometry and viewpoint, so an object can be simultaneously recognized and registered in a stable pose and the information is stored in a database. The VFH is robust to a large degree of surface noise and missing depth information so it is reliable for stereo data. However, the pose estimation for an object fails when the object is placed symmetrically to the viewpoint. To overcome this problem, this study proposes a modified viewpoint feature histogram (MVFH) descriptor that consists of two parts: a surface shape component that comprises an extended fast point feature histogram and an extended viewpoint direction component. The MVFH descriptor characterizes an object’s pose and enhances the system’s ability to identify objects with mirrored poses. Finally, the refined pose is further estimated using an iterative closest point when the object has been recognized and the pose roughly estimated by the MVFH descriptor and it has been registered on a database. The estimation results demonstrate that the MVFH feature descriptor allows more accurate pose estimation. The experiments also show that the proposed method can be applied in vision-guided robotic grasping systems. PMID:27886080

Refining atmosphere light to improve the dark channel prior algorithm

NASA Astrophysics Data System (ADS)

Gan, Ling; Li, Dagang; Zhou, Can

2017-05-01

The defogging image gotten through dark channel prior algorithm has some shortcomings, such like color distortion, dimmer light and detail-loss near the observer. The main reasons are that the atmosphere light is estimated as one value and its change in different scene depth is not considered. So we modeled the atmosphere, one parameter of the defogging model. Firstly, we scatter the atmosphere light into equivalent point and build discrete model of the light. Secondly, we build some rough and possible models through analyzing the relationship between the atmosphere light and the medium transmission. Finally, by analyzing the results of many experiments qualitatively and quantitatively, we get the selected and optimized model. Although using this method causes the time-consuming to increase slightly, the evaluations, histogram correlation coefficient and peak signal-to-noise ratio are improved significantly and the defogging result is more conformed to human visual. And the color and the details near the observer in the defogging image are better than that achieved by the primal method.

n-SIFT: n-dimensional scale invariant feature transform.

PubMed

Cheung, Warren; Hamarneh, Ghassan

2009-09-01

We propose the n-dimensional scale invariant feature transform (n-SIFT) method for extracting and matching salient features from scalar images of arbitrary dimensionality, and compare this method's performance to other related features. The proposed features extend the concepts used for 2-D scalar images in the computer vision SIFT technique for extracting and matching distinctive scale invariant features. We apply the features to images of arbitrary dimensionality through the use of hyperspherical coordinates for gradients and multidimensional histograms to create the feature vectors. We analyze the performance of a fully automated multimodal medical image matching technique based on these features, and successfully apply the technique to determine accurate feature point correspondence between pairs of 3-D MRI images and dynamic 3D + time CT data.

Reconnection at the earth's magnetopause - Magnetic field observations and flux transfer events

NASA Technical Reports Server (NTRS)

Russell, C. T.

1984-01-01

Theoretical models of plasma acceleration by magnetic-field-line reconnection at the earth magnetopause and the high-resolution three-dimensional plasma measurements obtained with the ISEE satellites are compared and illustrated with diagrams, graphs, drawings, and histograms. The history of reconnection theory and the results of early satellite observations are summarized; the thickness of the magnetopause current layer is discussed; problems in analyzing the polarization of current-layer rotation are considered; and the flux-transfer events responsible for periods of patchy reconnection are characterized in detail. The need for further observations and refinements of the theory to explain the initiation of reconnection and identify the mechanism determining whether it is patchy or steady-state is indicated.

THTM: A template matching algorithm based on HOG descriptor and two-stage matching

NASA Astrophysics Data System (ADS)

Jiang, Yuanjie; Ruan, Li; Xiao, Limin; Liu, Xi; Yuan, Feng; Wang, Haitao

2018-04-01

We propose a novel method for template matching named THTM - a template matching algorithm based on HOG (histogram of gradient) and two-stage matching. We rely on the fast construction of HOG and the two-stage matching that jointly lead to a high accuracy approach for matching. TMTM give enough attention on HOG and creatively propose a twice-stage matching while traditional method only matches once. Our contribution is to apply HOG to template matching successfully and present two-stage matching, which is prominent to improve the matching accuracy based on HOG descriptor. We analyze key features of THTM and perform compared to other commonly used alternatives on a challenging real-world datasets. Experiments show that our method outperforms the comparison method.

FEWZ 2.0: A code for hadronic Z production at next-to-next-to-leading order

NASA Astrophysics Data System (ADS)

Gavin, Ryan; Li, Ye; Petriello, Frank; Quackenbush, Seth

2011-11-01

We introduce an improved version of the simulation code FEWZ ( Fully Exclusive W and Z Production) for hadron collider production of lepton pairs through the Drell-Yan process at next-to-next-to-leading order (NNLO) in the strong coupling constant. The program is fully differential in the phase space of leptons and additional hadronic radiation. The new version offers users significantly more options for customization. FEWZ now bins multiple, user-selectable histograms during a single run, and produces parton distribution function (PDF) errors automatically. It also features a significantly improved integration routine, and can take advantage of multiple processor cores locally or on the Condor distributed computing system. We illustrate the new features of FEWZ by presenting numerous phenomenological results for LHC physics. We compare NNLO QCD with initial ATLAS and CMS results, and discuss in detail the effects of detector acceptance on the measurement of angular quantities associated with Z-boson production. We address the issue of technical precision in the presence of severe phase-space cuts. Program summaryProgram title: FEWZ Catalogue identifier: AEJP_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJP_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 6 280 771 No. of bytes in distributed program, including test data, etc.: 173 027 645 Distribution format: tar.gz Programming language: Fortran 77, C++, Python Computer: Mac, PC Operating system: Mac OSX, Unix/Linux Has the code been vectorized or parallelized?: Yes. User-selectable, 1 to 219 RAM: 200 Mbytes for common parton distribution functions Classification: 11.1 External routines: CUBA numerical integration library, numerous parton distribution sets (see text); these are provided with the code. Nature of problem: Determination of the Drell-Yan Z/photon production cross section and decay into leptons, with kinematic distributions of leptons and jets including full spin correlations, at next-to-next-to-leading order in the strong coupling constant. Solution method: Virtual loop integrals are decomposed into master integrals using automated techniques. Singularities are extracted from real radiation terms via sector decomposition, which separates singularities and maps onto suitable phase space variables. Result is convoluted with parton distribution functions. Each piece is numerically integrated over phase space, which allows arbitrary cuts on the observed particles. Each sample point may be binned during numerical integration, providing histograms, and reweighted by parton distribution function error eigenvectors, which provides PDF errors. Restrictions: Output does not correspond to unweighted events, and cannot be interfaced with a shower Monte Carlo. Additional comments: !!!!! The distribution file for this program is over 170 Mbytes and therefore is not delivered directly when download or E-mail is requested. Instead a html file giving details of how the program can be obtained is sent. Running time: One day for total cross sections with 0.1% integration errors assuming typical cuts, up to 1 week for smooth kinematic distributions with sub-percent integration errors for each bin.

Apparent Diffusion Coefficient Histograms of Human Papillomavirus-Positive and Human Papillomavirus-Negative Head and Neck Squamous Cell Carcinoma: Assessment of Tumor Heterogeneity and Comparison with Histopathology.

PubMed

de Perrot, T; Lenoir, V; Domingo Ayllón, M; Dulguerov, N; Pusztaszeri, M; Becker, M

2017-11-01

Head and neck squamous cell carcinoma associated with human papillomavirus infection represents a distinct tumor entity. We hypothesized that diffusion phenotypes based on the histogram analysis of ADC values reflect distinct degrees of tumor heterogeneity in human papillomavirus-positive and human papillomavirus-negative head and neck squamous cell carcinomas. One hundred five consecutive patients (mean age, 64 years; range, 45-87 years) with primary oropharyngeal ( n = 52) and oral cavity ( n = 53) head and neck squamous cell carcinoma underwent MR imaging with anatomic and diffusion-weighted sequences ( b = 0, b = 1000 s/mm 2 , monoexponential ADC calculation). The collected tumor voxels from the contoured ROIs provided histograms from which position, dispersion, and form parameters were computed. Histogram data were correlated with histopathology, p16-immunohistochemistry, and polymerase chain reaction for human papillomavirus DNA. There were 21 human papillomavirus-positive and 84 human papillomavirus-negative head and neck squamous cell carcinomas. At histopathology, human papillomavirus-positive cancers were more often nonkeratinizing (13/21, 62%) than human papillomavirus-negative cancers (19/84, 23%; P = .001), and their mitotic index was higher (71% versus 49%; P = .005). ROI-based mean and median ADCs were significantly lower in human papillomavirus-positive (1014 ± 178 × 10 -6 mm 2 /s and 970 ± 187 × 10 -6 mm 2 /s, respectively) than in human papillomavirus-negative tumors (1184 ± 168 × 10 -6 mm 2 /s and 1161 ± 175 × 10 -6 mm 2 /s, respectively; P < .001), whereas excess kurtosis and skewness were significantly higher in human papillomavirus-positive (1.934 ± 1.386 and 0.923 ± 0.510, respectively) than in human papillomavirus-negative tumors (0.643 ± 0.982 and 0.399 ± 0.516, respectively; P < .001). Human papillomavirus-negative head and neck squamous cell carcinoma had symmetric normally distributed ADC histograms, which corresponded histologically to heterogeneous tumors with variable cellularity, high stromal component, keratin pearls, and necrosis. Human papillomavirus-positive head and neck squamous cell carcinomas had leptokurtic skewed right histograms, which corresponded to homogeneous tumors with back-to-back densely packed cells, scant stromal component, and scattered comedonecrosis. Diffusion phenotypes of human papillomavirus-positive and human papillomavirus-negative head and neck squamous cell carcinomas show significant differences, which reflect their distinct degree of tumor heterogeneity. © 2017 by American Journal of Neuroradiology.

Histogram analysis of apparent diffusion coefficient at 3.0 T in urinary bladder lesions: correlation with pathologic findings.

PubMed

Suo, Shi-Teng; Chen, Xiao-Xi; Fan, Yu; Wu, Lian-Ming; Yao, Qiu-Ying; Cao, Meng-Qiu; Liu, Qiang; Xu, Jian-Rong

2014-08-01

To investigate the potential value of histogram analysis of apparent diffusion coefficient (ADC) obtained at standard (700 s/mm(2)) and high (1500 s/mm(2)) b values on a 3.0-T scanner in the differentiation of bladder cancer from benign lesions and in assessing bladder tumors of different pathologic T stages and to evaluate the diagnostic performance of ADC-based histogram parameters. In all, 52 patients with bladder lesions, including benign lesions (n = 7) and malignant tumors (n = 45; T1 stage or less, 23; T2 stage, 7; T3 stage, 8; and T4 stage, 7), were retrospectively evaluated. Magnetic resonance examination at 3.0 T and diffusion-weighted imaging were performed. ADC maps were obtained at two b values (b = 700 and 1500 s/mm(2); ie, ADC-700 and ADC-1500). Parameters of histogram analysis included mean, kurtosis, skewness, and entropy. The correlations between these parameters and pathologic results were revealed. Receiver operating characteristic (ROC) curves were generated to determine the diagnostic value of histogram parameters. Significant differences were found in mean ADC-700, mean ADC-1500, skewness ADC-1500, and kurtosis ADC-1500 between bladder cancer and benign lesions (P = .002-.032). There were also significant differences in mean ADC-700, mean ADC-1500, and kurtosis ADC-1500 among bladder tumors of different pathologic T stages (P = .000-.046). No significant differences were observed in other parameters. Mean ADC-1500 and kurtosis ADC-1500 were significantly correlated with T stage, respectively (ρ = -0.614, P < .001; ρ = 0.374, P = .011). ROC analysis showed that the combination of mean ADC-1500 and kurtosis ADC-1500 has the maximal area under the ROC curve (AUC, 0.894; P < .001) in the differentiation of benign lesions and malignant tumors, with a sensitivity of 77.78% and specificity of 100%. AUCs for differentiating low- and high-stage tumors were 0.840 for mean ADC-1500 (P < .001) and 0.696 for kurtosis ADC-1500 (P = .015). Histogram analysis of ADC-1500 at 3.0 T can be useful in evaluation of bladder lesions. A combination of mean ADC-1500 and kurtosis ADC-1500 may be more beneficial in the differentiation of benign and malignant lesions. Mean ADC-1500 was the most promising parameter for differentiating low- from high-stage bladder cancer. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Measuring kinetics of complex single ion channel data using mean-variance histograms.

PubMed Central

Patlak, J B

1993-01-01

The measurement of single ion channel kinetics is difficult when those channels exhibit subconductance events. When the kinetics are fast, and when the current magnitudes are small, as is the case for Na+, Ca2+, and some K+ channels, these difficulties can lead to serious errors in the estimation of channel kinetics. I present here a method, based on the construction and analysis of mean-variance histograms, that can overcome these problems. A mean-variance histogram is constructed by calculating the mean current and the current variance within a brief "window" (a set of N consecutive data samples) superimposed on the digitized raw channel data. Systematic movement of this window over the data produces large numbers of mean-variance pairs which can be assembled into a two-dimensional histogram. Defined current levels (open, closed, or sublevel) appear in such plots as low variance regions. The total number of events in such low variance regions is estimated by curve fitting and plotted as a function of window width. This function decreases with the same time constants as the original dwell time probability distribution for each of the regions. The method can therefore be used: 1) to present a qualitative summary of the single channel data from which the signal-to-noise ratio, open channel noise, steadiness of the baseline, and number of conductance levels can be quickly determined; 2) to quantify the dwell time distribution in each of the levels exhibited. In this paper I present the analysis of a Na+ channel recording that had a number of complexities. The signal-to-noise ratio was only about 8 for the main open state, open channel noise, and fast flickers to other states were present, as were a substantial number of subconductance states. "Standard" half-amplitude threshold analysis of these data produce open and closed time histograms that were well fitted by the sum of two exponentials, but with apparently erroneous time constants, whereas the mean-variance histogram technique provided a more credible analysis of the open, closed, and subconductance times for the patch. I also show that the method produces accurate results on simulated data in a wide variety of conditions, whereas the half-amplitude method, when applied to complex simulated data shows the same errors as were apparent in the real data. The utility and the limitations of this new method are discussed. Images FIGURE 2 FIGURE 4 FIGURE 8 FIGURE 9 PMID:7690261

Digital enhancement of computerized axial tomograms

NASA Technical Reports Server (NTRS)

Roberts, E., Jr.

1978-01-01

A systematic evaluation has been conducted of certain digital image enhancement techniques performed in image space. Three types of images have been used, computer generated phantoms, tomograms of a synthetic phantom, and axial tomograms of human anatomy containing images of lesions, artificially introduced into the tomograms. Several types of smoothing, sharpening, and histogram modification have been explored. It has been concluded that the most useful enhancement techniques are a selective smoothing of singular picture elements, combined with contrast manipulation. The most useful tool in applying these techniques is the gray-scale histogram.

Double Negative (CD3+4-8-) TCRalphaBeta Splenic Cells from Young NOD Mice Provide Long-Lasting Protection against Type 1 Diabetes

DTIC Science & Technology

2010-07-02

indicated. Panel B, pancreatic infiltrating lymphocytes from 4 month-old NOD females ( left histogram) and males ( right histogram) (n = 8 mice/group...assay was used to measure the IL-2 secretion in the culture medium. Panel A, DN splenic cell cultures stimulated under Th1 ( left panel) and Th2 ( right ...variance test. The significance (p#0.005) of individual differences in frequency of DNCD3 thymocytes and splenocytes from female and male NOD littermates

Better Than Counting: Density Profiles from Force Sampling

NASA Astrophysics Data System (ADS)

de las Heras, Daniel; Schmidt, Matthias

2018-05-01

Calculating one-body density profiles in equilibrium via particle-based simulation methods involves counting of events of particle occurrences at (histogram-resolved) space points. Here, we investigate an alternative method based on a histogram of the local force density. Via an exact sum rule, the density profile is obtained with a simple spatial integration. The method circumvents the inherent ideal gas fluctuations. We have tested the method in Monte Carlo, Brownian dynamics, and molecular dynamics simulations. The results carry a statistical uncertainty smaller than that of the standard counting method, reducing therefore the computation time.

Shell structures in aluminum nanocontacts at elevated temperatures

PubMed Central

2012-01-01

Aluminum nanocontact conductance histograms are studied experimentally from room temperature up to near the bulk melting point. The dominant stable configurations for this metal show a very early crossover from shell structures at low wire diameters to ionic subshell structures at larger diameters. At these larger radii, the favorable structures are temperature-independent and consistent with those expected for ionic subshell (faceted) formations in face-centered cubic geometries. When approaching the bulk melting temperature, these local stability structures become less pronounced as shown by the vanishing conductance histogram peak structure. PMID:22325572

Cross-platform validation and analysis environment for particle physics

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

Chekanov, S. V.; Pogrebnyak, I.; Wilbern, D.

A multi-platform validation and analysis framework for public Monte Carlo simulation for high-energy particle collisions is discussed. The front-end of this framework uses the Python programming language, while the back-end is written in Java, which provides a multi-platform environment that can be run from a web browser and can easily be deployed at the grid sites. The analysis package includes all major software tools used in high-energy physics, such as Lorentz vectors, jet algorithms, histogram packages, graphic canvases, and tools for providing data access. This multi-platform software suite, designed to minimize OS-specific maintenance and deployment time, is used for onlinemore » validation of Monte Carlo event samples through a web interface.« less

Whole-lesion histogram analysis of the apparent diffusion coefficient: Evaluation of the correlation with subtypes of mucinous breast carcinoma.

PubMed

Guo, Yuan; Kong, Qing-Cong; Zhu, Ye-Qing; Liu, Zhen-Zhen; Peng, Ling-Rong; Tang, Wen-Jie; Yang, Rui-Meng; Xie, Jia-Jun; Liu, Chun-Ling

2018-02-01

To evaluate the utility of the whole-lesion histogram apparent diffusion coefficient (ADC) for characterizing the heterogeneity of mucinous breast carcinoma (MBC) and to determine which ADC metrics may help to best differentiate subtypes of MBC. This retrospective study involved 52 MBC patients, including 37 pure MBC (PMBC) and 15 mixed MBC (MMBC). The PMBC patients were subtyped into PMBC-A (20 cases) and PMBC-B (17 cases) groups. All patients underwent preoperative diffusion-weighted imaging (DWI) at 1.5T and the whole-lesion ADC assessments were generated. Histogram-derived ADC parameters were compared between PMBC vs. MMBC and PMBC-A vs. PMBC-B, and receiver operating characteristic (ROC) curve analysis was used to determine optimal histogram parameters for differentiating these groups. The PMBC group exhibited significantly higher ADC values for the mean (P = 0.004), 25 th (P = 0.004), 50 th (P = 0.004), 75 th (P = 0.006), and 90 th percentiles (P = 0.013) and skewness (P = 0.021) than did the MMBC group. The 25 th percentile of ADC values achieved the highest area under the curve (AUC) (0.792), with a cutoff value of 1.345 × 10 -3 mm 2 /s, in distinguishing PMBC and MMBC. The PMBC-A group showed significantly higher ADC values for the mean (P = 0.049), 25 th (P = 0.015), and 50 th (P = 0.026) percentiles and skewness (P = 0.004) than did the PMBC-B group. The 25 th percentile of the ADC cutoff value (1.476 × 10 -3 mm 2 /s) demonstrated the best AUC (0.837) among the ADC values for distinguishing PMBC-A and PMBC-B. Whole-lesion ADC histogram analysis enables comprehensive evaluation of an MBC in its entirety and differentiating subtypes of MBC. Thus, it may be a helpful and supportive tool for conventional MRI. 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:391-400. © 2017 International Society for Magnetic Resonance in Medicine.

Quantitative Evaluation for Differentiating Malignant and Benign Thyroid Nodules Using Histogram Analysis of Grayscale Sonograms.

PubMed

Nam, Se Jin; Yoo, Jaeheung; Lee, Hye Sun; Kim, Eun-Kyung; Moon, Hee Jung; Yoon, Jung Hyun; Kwak, Jin Young

2016-04-01

To evaluate the diagnostic value of histogram analysis using grayscale sonograms for differentiation of malignant and benign thyroid nodules. From July 2013 through October 2013, 579 nodules in 563 patients who had undergone ultrasound-guided fine-needle aspiration were included. For the grayscale histogram analysis, pixel echogenicity values in regions of interest were measured as 0 to 255 (0, black; 255, white) with in-house software. Five parameters (mean, skewness, kurtosis, standard deviation, and entropy) were obtained for each thyroid nodule. With principal component analysis, an index was derived. Diagnostic performance rates for the 5 histogram parameters and the principal component analysis index were calculated. A total of 563 patients were included in the study (mean age ± SD, 50.3 ± 12.3 years;range, 15-79 years). Of the 579 nodules, 431 were benign, and 148 were malignant. Among the 5 parameters and the principal component analysis index, the standard deviation (75.546 ± 14.153 versus 62.761 ± 16.01; P < .001), kurtosis (3.898 ± 2.652 versus 6.251 ± 9.102; P < .001), entropy (0.16 ± 0.135 versus 0.239 ± 0.185; P < .001), and principal component analysis index (-0.386±0.774 versus 0.134 ± 0.889; P < .001) were significantly different between the malignant and benign nodules. With the calculated cutoff values, the areas under the curve were 0.681 (95% confidence interval, 0.643-0.721) for standard deviation, 0.661 (0.620-0.703) for principal component analysis index, 0.651 (0.607-0.691) for kurtosis, 0.638 (0.596-0.681) for entropy, and 0.606 (0.563-0.647) for skewness. The subjective analysis of grayscale sonograms by radiologists alone showed an area under the curve of 0.861 (0.833-0.888). Grayscale histogram analysis was feasible for differentiating malignant and benign thyroid nodules but did not show better diagnostic performance than subjective analysis performed by radiologists. Further technical advances will be needed to objectify interpretations of thyroid grayscale sonograms. © 2016 by the American Institute of Ultrasound in Medicine.

Improved dose-volume histogram estimates for radiopharmaceutical therapy by optimizing quantitative SPECT reconstruction parameters

NASA Astrophysics Data System (ADS)

Cheng, Lishui; Hobbs, Robert F.; Segars, Paul W.; Sgouros, George; Frey, Eric C.

2013-06-01

In radiopharmaceutical therapy, an understanding of the dose distribution in normal and target tissues is important for optimizing treatment. Three-dimensional (3D) dosimetry takes into account patient anatomy and the nonuniform uptake of radiopharmaceuticals in tissues. Dose-volume histograms (DVHs) provide a useful summary representation of the 3D dose distribution and have been widely used for external beam treatment planning. Reliable 3D dosimetry requires an accurate 3D radioactivity distribution as the input. However, activity distribution estimates from SPECT are corrupted by noise and partial volume effects (PVEs). In this work, we systematically investigated OS-EM based quantitative SPECT (QSPECT) image reconstruction in terms of its effect on DVHs estimates. A modified 3D NURBS-based Cardiac-Torso (NCAT) phantom that incorporated a non-uniform kidney model and clinically realistic organ activities and biokinetics was used. Projections were generated using a Monte Carlo (MC) simulation; noise effects were studied using 50 noise realizations with clinical count levels. Activity images were reconstructed using QSPECT with compensation for attenuation, scatter and collimator-detector response (CDR). Dose rate distributions were estimated by convolution of the activity image with a voxel S kernel. Cumulative DVHs were calculated from the phantom and QSPECT images and compared both qualitatively and quantitatively. We found that noise, PVEs, and ringing artifacts due to CDR compensation all degraded histogram estimates. Low-pass filtering and early termination of the iterative process were needed to reduce the effects of noise and ringing artifacts on DVHs, but resulted in increased degradations due to PVEs. Large objects with few features, such as the liver, had more accurate histogram estimates and required fewer iterations and more smoothing for optimal results. Smaller objects with fine details, such as the kidneys, required more iterations and less smoothing at early time points post-radiopharmaceutical administration but more smoothing and fewer iterations at later time points when the total organ activity was lower. The results of this study demonstrate the importance of using optimal reconstruction and regularization parameters. Optimal results were obtained with different parameters at each time point, but using a single set of parameters for all time points produced near-optimal dose-volume histograms.

The analysis of polar clouds from AVHRR satellite data using pattern recognition techniques

NASA Technical Reports Server (NTRS)

Smith, William L.; Ebert, Elizabeth

1990-01-01

The cloud cover in a set of summertime and wintertime AVHRR data from the Arctic and Antarctic regions was analyzed using a pattern recognition algorithm. The data were collected by the NOAA-7 satellite on 6 to 13 Jan. and 1 to 7 Jul. 1984 between 60 deg and 90 deg north and south latitude in 5 spectral channels, at the Global Area Coverage (GAC) resolution of approximately 4 km. This data embodied a Polar Cloud Pilot Data Set which was analyzed by a number of research groups as part of a polar cloud algorithm intercomparison study. This study was intended to determine whether the additional information contained in the AVHRR channels (beyond the standard visible and infrared bands on geostationary satellites) could be effectively utilized in cloud algorithms to resolve some of the cloud detection problems caused by low visible and thermal contrasts in the polar regions. The analysis described makes use of a pattern recognition algorithm which estimates the surface and cloud classification, cloud fraction, and surface and cloudy visible (channel 1) albedo and infrared (channel 4) brightness temperatures on a 2.5 x 2.5 deg latitude-longitude grid. In each grid box several spectral and textural features were computed from the calibrated pixel values in the multispectral imagery, then used to classify the region into one of eighteen surface and/or cloud types using the maximum likelihood decision rule. A slightly different version of the algorithm was used for each season and hemisphere because of differences in categories and because of the lack of visible imagery during winter. The classification of the scene is used to specify the optimal AVHRR channel for separating clear and cloudy pixels using a hybrid histogram-spatial coherence method. This method estimates values for cloud fraction, clear and cloudy albedos and brightness temperatures in each grid box. The choice of a class-dependent AVHRR channel allows for better separation of clear and cloudy pixels than does a global choice of a visible and/or infrared threshold. The classification also prevents erroneous estimates of large fractional cloudiness in areas of cloudfree snow and sea ice. The hybrid histogram-spatial coherence technique and the advantages of first classifying a scene in the polar regions are detailed. The complete Polar Cloud Pilot Data Set was analyzed and the results are presented and discussed.

Document image cleanup and binarization

NASA Astrophysics Data System (ADS)

Wu, Victor; Manmatha, Raghaven

1998-04-01

Image binarization is a difficult task for documents with text over textured or shaded backgrounds, poor contrast, and/or considerable noise. Current optical character recognition (OCR) and document analysis technology do not handle such documents well. We have developed a simple yet effective algorithm for document image clean-up and binarization. The algorithm consists of two basic steps. In the first step, the input image is smoothed using a low-pass filter. The smoothing operation enhances the text relative to any background texture. This is because background texture normally has higher frequency than text does. The smoothing operation also removes speckle noise. In the second step, the intensity histogram of the smoothed image is computed and a threshold automatically selected as follows. For black text, the first peak of the histogram corresponds to text. Thresholding the image at the value of the valley between the first and second peaks of the histogram binarizes the image well. In order to reliably identify the valley, the histogram is smoothed by a low-pass filter before the threshold is computed. The algorithm has been applied to some 50 images from a wide variety of source: digitized video frames, photos, newspapers, advertisements in magazines or sales flyers, personal checks, etc. There are 21820 characters and 4406 words in these images. 91 percent of the characters and 86 percent of the words are successfully cleaned up and binarized. A commercial OCR was applied to the binarized text when it consisted of fonts which were OCR recognizable. The recognition rate was 84 percent for the characters and 77 percent for the words.

Investigating the Role of Global Histogram Equalization Technique for 99mTechnetium-Methylene diphosphonate Bone Scan Image Enhancement.

PubMed

Pandey, Anil Kumar; Sharma, Param Dev; Dheer, Pankaj; Parida, Girish Kumar; Goyal, Harish; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-01-01

99m Technetium-methylene diphosphonate ( 99m Tc-MDP) bone scan images have limited number of counts per pixel, and hence, they have inferior image quality compared to X-rays. Theoretically, global histogram equalization (GHE) technique can improve the contrast of a given image though practical benefits of doing so have only limited acceptance. In this study, we have investigated the effect of GHE technique for 99m Tc-MDP-bone scan images. A set of 89 low contrast 99m Tc-MDP whole-body bone scan images were included in this study. These images were acquired with parallel hole collimation on Symbia E gamma camera. The images were then processed with histogram equalization technique. The image quality of input and processed images were reviewed by two nuclear medicine physicians on a 5-point scale where score of 1 is for very poor and 5 is for the best image quality. A statistical test was applied to find the significance of difference between the mean scores assigned to input and processed images. This technique improves the contrast of the images; however, oversaturation was noticed in the processed images. Student's t -test was applied, and a statistically significant difference in the input and processed image quality was found at P < 0.001 (with α = 0.05). However, further improvement in image quality is needed as per requirements of nuclear medicine physicians. GHE techniques can be used on low contrast bone scan images. In some of the cases, a histogram equalization technique in combination with some other postprocessing technique is useful.

Automatic discrimination of color retinal images using the bag of words approach

NASA Astrophysics Data System (ADS)

Sadek, I.; Sidibé, D.; Meriaudeau, F.

2015-03-01

Diabetic retinopathy (DR) and age related macular degeneration (ARMD) are among the major causes of visual impairment all over the world. DR is mainly characterized by small red spots, namely microaneurysms and bright lesions, specifically exudates. However, ARMD is mainly identified by tiny yellow or white deposits called drusen. Since exudates might be the only visible signs of the early diabetic retinopathy, there is an increase demand for automatic diagnosis of retinopathy. Exudates and drusen may share similar appearances; as a result discriminating between them plays a key role in improving screening performance. In this research, we investigative the role of bag of words approach in the automatic diagnosis of retinopathy diabetes. Initially, the color retinal images are preprocessed in order to reduce the intra and inter patient variability. Subsequently, SURF (Speeded up Robust Features), HOG (Histogram of Oriented Gradients), and LBP (Local Binary Patterns) descriptors are extracted. We proposed to use single-based and multiple-based methods to construct the visual dictionary by combining the histogram of word occurrences from each dictionary and building a single histogram. Finally, this histogram representation is fed into a support vector machine with linear kernel for classification. The introduced approach is evaluated for automatic diagnosis of normal and abnormal color retinal images with bright lesions such as drusen and exudates. This approach has been implemented on 430 color retinal images, including six publicly available datasets, in addition to one local dataset. The mean accuracies achieved are 97.2% and 99.77% for single-based and multiple-based dictionaries respectively.

Postmortem validation of breast density using dual-energy mammography

PubMed Central

Molloi, Sabee; Ducote, Justin L.; Ding, Huanjun; Feig, Stephen A.

2014-01-01

Purpose: Mammographic density has been shown to be an indicator of breast cancer risk and also reduces the sensitivity of screening mammography. Currently, there is no accepted standard for measuring breast density. Dual energy mammography has been proposed as a technique for accurate measurement of breast density. The purpose of this study is to validate its accuracy in postmortem breasts and compare it with other existing techniques. Methods: Forty postmortem breasts were imaged using a dual energy mammography system. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Dual energy decomposition was applied after scatter correction to calculate breast density. Breast density was also estimated using radiologist reader assessment, standard histogram thresholding and a fuzzy C-mean algorithm. Chemical analysis was used as the reference standard to assess the accuracy of different techniques to measure breast composition. Results: Breast density measurements using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and dual energy were in good agreement with the measured fibroglandular volume fraction using chemical analysis. The standard error estimates using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean, and dual energy were 9.9%, 8.6%, 7.2%, and 4.7%, respectively. Conclusions: The results indicate that dual energy mammography can be used to accurately measure breast density. The variability in breast density estimation using dual energy mammography was lower than reader assessment rankings, standard histogram thresholding, and fuzzy C-mean algorithm. Improved quantification of breast density is expected to further enhance its utility as a risk factor for breast cancer. PMID:25086548

Postmortem validation of breast density using dual-energy mammography

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

Molloi, Sabee, E-mail: symolloi@uci.edu; Ducote, Justin L.; Ding, Huanjun

2014-08-15

Purpose: Mammographic density has been shown to be an indicator of breast cancer risk and also reduces the sensitivity of screening mammography. Currently, there is no accepted standard for measuring breast density. Dual energy mammography has been proposed as a technique for accurate measurement of breast density. The purpose of this study is to validate its accuracy in postmortem breasts and compare it with other existing techniques. Methods: Forty postmortem breasts were imaged using a dual energy mammography system. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Dual energy decompositionmore » was applied after scatter correction to calculate breast density. Breast density was also estimated using radiologist reader assessment, standard histogram thresholding and a fuzzy C-mean algorithm. Chemical analysis was used as the reference standard to assess the accuracy of different techniques to measure breast composition. Results: Breast density measurements using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and dual energy were in good agreement with the measured fibroglandular volume fraction using chemical analysis. The standard error estimates using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean, and dual energy were 9.9%, 8.6%, 7.2%, and 4.7%, respectively. Conclusions: The results indicate that dual energy mammography can be used to accurately measure breast density. The variability in breast density estimation using dual energy mammography was lower than reader assessment rankings, standard histogram thresholding, and fuzzy C-mean algorithm. Improved quantification of breast density is expected to further enhance its utility as a risk factor for breast cancer.« less

An Apparent Diffusion Coefficient Histogram Method Versus a Traditional 2-Dimensional Measurement Method for Identifying Non-Puerperal Mastitis From Breast Cancer at 3.0 T.

PubMed

Tang, Qi; Li, Qiang; Xie, Dong; Chu, Ketao; Liu, Lidong; Liao, Chengcheng; Qin, Yunying; Wang, Zheng; Su, Danke

2018-05-21

This study aimed to investigate the utility of a volumetric apparent diffusion coefficient (ADC) histogram method for distinguishing non-puerperal mastitis (NPM) from breast cancer (BC) and to compare this method with a traditional 2-dimensional measurement method. Pretreatment diffusion-weighted imaging data at 3.0 T were obtained for 80 patients (NPM, n = 27; BC, n = 53) and were retrospectively assessed. Two readers measured ADC values according to 2 distinct region-of-interest (ROI) protocols. The first protocol included the generation of ADC histograms for each lesion, and various parameters were examined. In the second protocol, 3 freehand (TF) ROIs for local lesions were generated to obtain a mean ADC value (defined as ADC-ROITF). All of the ADC values were compared by an independent-samples t test or the Mann-Whitney U test. Receiver operating characteristic curves and a leave-one-out cross-validation method were also used to determine diagnostic deficiencies of the significant parameters. The ADC values for NPM were characterized by significantly higher mean, 5th to 95th percentiles, and maximum and mode ADCs compared with the corresponding ADCs for BC (all P < 0.05). However, the minimum, skewness, and kurtosis ADC values, as well as ADC-ROITF, did not significantly differ between the NPM and BC cases. Thus, the generation of volumetric ADC histograms seems to be a superior method to the traditional 2-dimensional method that was examined, and it also seems to represent a promising image analysis method for distinguishing NPM from BC.

WebGL and web audio software lightweight components for multimedia education

NASA Astrophysics Data System (ADS)

Chang, Xin; Yuksel, Kivanc; Skarbek, Władysław

2017-08-01

The paper presents the results of our recent work on development of contemporary computing platform DC2 for multimedia education usingWebGL andWeb Audio { the W3C standards. Using literate programming paradigm the WEBSA educational tools were developed. It offers for a user (student), the access to expandable collection of WEBGL Shaders and web Audio scripts. The unique feature of DC2 is the option of literate programming, offered for both, the author and the reader in order to improve interactivity to lightweightWebGL andWeb Audio components. For instance users can define: source audio nodes including synthetic sources, destination audio nodes, and nodes for audio processing such as: sound wave shaping, spectral band filtering, convolution based modification, etc. In case of WebGL beside of classic graphics effects based on mesh and fractal definitions, the novel image processing analysis by shaders is offered like nonlinear filtering, histogram of gradients, and Bayesian classifiers.