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

Histogram Curve Matching Approaches for Object-based Image Classification of Land Cover and Land Use

PubMed Central

Toure, Sory I.; Stow, Douglas A.; Weeks, John R.; Kumar, Sunil

2013-01-01

The classification of image-objects is usually done using parametric statistical measures of central tendency and/or dispersion (e.g., mean or standard deviation). The objectives of this study were to analyze digital number histograms of image objects and evaluate classifications measures exploiting characteristic signatures of such histograms. Two histograms matching classifiers were evaluated and compared to the standard nearest neighbor to mean classifier. An ADS40 airborne multispectral image of San Diego, California was used for assessing the utility of curve matching classifiers in a geographic object-based image analysis (GEOBIA) approach. The classifications were performed with data sets having 0.5 m, 2.5 m, and 5 m spatial resolutions. Results show that histograms are reliable features for characterizing classes. Also, both histogram matching classifiers consistently performed better than the one based on the standard nearest neighbor to mean rule. The highest classification accuracies were produced with images having 2.5 m spatial resolution. PMID:24403648

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.

Improved automatic adjustment of density and contrast in FCR system using neural network

NASA Astrophysics Data System (ADS)

Takeo, Hideya; Nakajima, Nobuyoshi; Ishida, Masamitsu; Kato, Hisatoyo

1994-05-01

FCR system has an automatic adjustment of image density and contrast by analyzing the histogram of image data in the radiation field. Advanced image recognition methods proposed in this paper can improve the automatic adjustment performance, in which neural network technology is used. There are two methods. Both methods are basically used 3-layer neural network with back propagation. The image data are directly input to the input-layer in one method and the histogram data is input in the other method. The former is effective to the imaging menu such as shoulder joint in which the position of interest region occupied on the histogram changes by difference of positioning and the latter is effective to the imaging menu such as chest-pediatrics in which the histogram shape changes by difference of positioning. We experimentally confirm the validity of these methods (about the automatic adjustment performance) as compared with the conventional histogram analysis methods.

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.

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

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.

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

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.

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…

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.

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.

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.

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.

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.

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.

Comparative study of standard space and real space analysis of quantitative MR brain data.

PubMed

Aribisala, Benjamin S; He, Jiabao; Blamire, Andrew M

2011-06-01

To compare the robustness of region of interest (ROI) analysis of magnetic resonance imaging (MRI) brain data in real space with analysis in standard space and to test the hypothesis that standard space image analysis introduces more partial volume effect errors compared to analysis of the same dataset in real space. Twenty healthy adults with no history or evidence of neurological diseases were recruited; high-resolution T(1)-weighted, quantitative T(1), and B(0) field-map measurements were collected. Algorithms were implemented to perform analysis in real and standard space and used to apply a simple standard ROI template to quantitative T(1) datasets. Regional relaxation values and histograms for both gray and white matter tissues classes were then extracted and compared. Regional mean T(1) values for both gray and white matter were significantly lower using real space compared to standard space analysis. Additionally, regional T(1) histograms were more compact in real space, with smaller right-sided tails indicating lower partial volume errors compared to standard space analysis. Standard space analysis of quantitative MRI brain data introduces more partial volume effect errors biasing the analysis of quantitative data compared to analysis of the same dataset in real space. Copyright © 2011 Wiley-Liss, Inc.

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.

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.

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.

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.

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.

Whole-lesion histogram analysis metrics of the apparent diffusion coefficient as a marker of breast lesions characterization at 1.5 T.

PubMed

Bougias, H; Ghiatas, A; Priovolos, D; Veliou, K; Christou, A

2017-05-01

To retrospectively assess the role of whole-lesion apparent diffusion coefficient (ADC) in the characterization of breast tumors by comparing different histogram metrics. 49 patients with 53 breast lesions underwent magnetic resonance imaging (MRI). ADC histogram parameters, including the mean, mode, 10th/50th/90th percentile, skewness, kurtosis, and entropy ADCs, were derived for the whole-lesion volume in each patient. Mann-Whitney U-test, area under the receiver-operating characteristic curve (AUC) were used for statistical analysis. The mean, mode and 10th/50th/90th percentile ADC values were significantly lower in malignant lesions compared with benign ones (all P < 0.0001), while skewness was significantly higher in malignant lesions P = 0.02. However, no significant difference was found between entropy and kurtosis values in malignant lesions compared with benign ones (P = 0.06 and P = 1.00, respectively). Univariate logistic regression showed that 10th and 50th percentile ADC yielded the highest AUC (0.985; 95% confidence interval [CI]: 0.902, 1.000 and 0.982; 95% confidence interval [CI]: 0.896, 1.000 respectively), whereas kurtosis value yielded the lowest AUC (0.500; 95% CI: 0.355, 0.645), indicating that 10th and 50th percentile ADC values may be more accurate for lesion discrimination. Whole-lesion ADC histogram analysis could be a helpful index in the characterization and differentiation between benign and malignant breast lesions with the 10th and 50th percentile ADC be the most accurate discriminators. Copyright © 2017 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

Histogram based analysis of lung perfusion of children after congenital diaphragmatic hernia repair.

PubMed

Kassner, Nora; Weis, Meike; Zahn, Katrin; Schaible, Thomas; Schoenberg, Stefan O; Schad, Lothar R; Zöllner, Frank G

2018-05-01

To investigate a histogram based approach to characterize the distribution of perfusion in the whole left and right lung by descriptive statistics and to show how histograms could be used to visually explore perfusion defects in two year old children after Congenital Diaphragmatic Hernia (CDH) repair. 28 children (age of 24.2±1.7months; all left sided hernia; 9 after extracorporeal membrane oxygenation therapy) underwent quantitative DCE-MRI of the lung. Segmentations of left and right lung were manually drawn to mask the calculated pulmonary blood flow maps and then to derive histograms for each lung side. Individual and group wise analysis of histograms of left and right lung was performed. Ipsilateral and contralateral lung show significant difference in shape and descriptive statistics derived from the histogram (Wilcoxon signed-rank test, p<0.05) on group wise and individual level. Subgroup analysis (patients with vs without ECMO therapy) showed no significant differences using histogram derived parameters. Histogram analysis can be a valuable tool to characterize and visualize whole lung perfusion of children after CDH repair. It allows for several possibilities to analyze the data, either describing the perfusion differences between the right and left lung but also to explore and visualize localized perfusion patterns in the 3D lung volume. Subgroup analysis will be possible given sufficient sample sizes. Copyright © 2017 Elsevier Inc. All rights reserved.

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

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.

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.

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.

Data Analysis and Graphing in an Introductory Physics Laboratory: Spreadsheet versus Statistics Suite

ERIC Educational Resources Information Center

Peterlin, Primoz

2010-01-01

Two methods of data analysis are compared: spreadsheet software and a statistics software suite. Their use is compared analysing data collected in three selected experiments taken from an introductory physics laboratory, which include a linear dependence, a nonlinear dependence and a histogram. The merits of each method are compared. (Contains 7…

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.

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.

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.

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

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.

Intravoxel Incoherent Motion–derived Histogram Metrics for Assessment of Response after Combined Chemotherapy and Radiation Therapy in Rectal Cancer: Initial Experience and Comparison between Single-Section and Volumetric Analyses

PubMed Central

Vargas, Hebert Alberto; Lakhman, Yulia; Sudre, Romain; Do, Richard K. G.; Bibeau, Frederic; Azria, David; Assenat, Eric; Molinari, Nicolas; Pierredon, Marie-Ange; Rouanet, Philippe; Guiu, Boris

2016-01-01

Purpose To determine the diagnostic performance of intravoxel incoherent motion (IVIM) parameters and apparent diffusion coefficient (ADC) to assess response to combined chemotherapy and radiation therapy (CRT) in patients with rectal cancer by using histogram analysis derived from whole-tumor volumes and single-section regions of interest (ROIs). Materials and Methods The institutional review board approved this retrospective study of 31 patients with rectal cancer who underwent magnetic resonance (MR) imaging before and after CRT, including diffusion-weighted imaging with 34 b values prior to surgery. Patient consent was not required. ADC, perfusion-related diffusion fraction (f), slow diffusion coefficient (D), and fast diffusion coefficient (D*) were calculated on MR images acquired before and after CRT by using biexponential fitting. ADC and IVIM histogram metrics and median values were obtained by using whole-tumor volume and single-section ROI analyses. All ADC and IVIM parameters obtained before and after CRT were compared with histopathologic findings by using t tests with Holm-Sidak correction. Receiver operating characteristic curves were generated to evaluate the diagnostic performance of IVIM parameters derived from whole-tumor volume and single-section ROIs for prediction of histopathologic response. Results Extreme values aside, results of histogram analysis of ADC and IVIM were equivalent to median values for tumor response assessment (P > .06). Prior to CRT, none of the median ADC and IVIM diffusion metrics correlated with subsequent tumor response (P > .36). Median D and ADC values derived from either whole-volume or single-section analysis increased significantly after CRT (P ≤ .01) and were significantly higher in good versus poor responders (P ≤ .02). Median IVIM f and D* values did not significantly change after CRT and were not associated with tumor response to CRT (P > .36). Interobserver agreement was excellent for whole-tumor volume analysis (range, 0.91–0.95) but was only moderate for single-section ROI analysis (range, 0.50–0.63). Conclusion Median D and ADC values obtained after CRT were useful for discrimination between good and poor responders. Histogram metrics did not add to the median values for assessment of tumor response. Volumetric analysis demonstrated better interobserver reproducibility when compared with single-section ROI analysis. © RSNA, 2016 Online supplemental material is available for this article. PMID:26919562

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.

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.

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.

Using Data Analysis to Explore Class Enrollment.

ERIC Educational Resources Information Center

Davis, Gretchen

1990-01-01

Describes classroom activities and shows that statistics is a practical tool for solving real problems. Presents a histogram, a stem plot, and a box plot to compare data involving class enrollments. (YP)

Alternative types of molecule-decorated atomic chains in Au–CO–Au single-molecule junctions

PubMed Central

Balogh, Zoltán; Makk, Péter

2015-01-01

Summary We investigate the formation and evolution of Au–CO single-molecule break junctions. The conductance histogram exhibits two distinct molecular configurations, which are further investigated by a combined statistical analysis. According to conditional histogram and correlation analysis these molecular configurations show strong anticorrelations with each other and with pure Au monoatomic junctions and atomic chains. We identify molecular precursor configurations with somewhat higher conductance, which are formed prior to single-molecule junctions. According to detailed length analysis two distinct types of molecule-affected chain-formation processes are observed, and we compare these results to former theoretical calculations considering bridge- and atop-type molecular configurations where the latter has reduced conductance due to destructive Fano interference. PMID:26199840

Alternative types of molecule-decorated atomic chains in Au-CO-Au single-molecule junctions.

PubMed

Balogh, Zoltán; Makk, Péter; Halbritter, András

2015-01-01

We investigate the formation and evolution of Au-CO single-molecule break junctions. The conductance histogram exhibits two distinct molecular configurations, which are further investigated by a combined statistical analysis. According to conditional histogram and correlation analysis these molecular configurations show strong anticorrelations with each other and with pure Au monoatomic junctions and atomic chains. We identify molecular precursor configurations with somewhat higher conductance, which are formed prior to single-molecule junctions. According to detailed length analysis two distinct types of molecule-affected chain-formation processes are observed, and we compare these results to former theoretical calculations considering bridge- and atop-type molecular configurations where the latter has reduced conductance due to destructive Fano interference.

Introducing parallelism to histogramming functions for GEM systems

NASA Astrophysics Data System (ADS)

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

2015-09-01

This article is an assessment of potential parallelization of histogramming algorithms in GEM detector system. Histogramming and preprocessing algorithms in MATLAB were analyzed with regard to adding parallelism. Preliminary implementation of parallel strip histogramming resulted in speedup. Analysis of algorithms parallelizability is presented. Overview of potential hardware and software support to implement parallel algorithm is discussed.

Environmental justice assessment for transportation : risk analysis

DOT National Transportation Integrated Search

1999-04-01

This paper presents methods of comparing populations and their racial/ethnic compositions using tabulations, histograms, and Chi Squared tests for statistical significance of differences found. Two examples of these methods are presented: comparison ...

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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

Novel Histogram Based Unsupervised Classification Technique to Determine Natural Classes From Biophysically Relevant Fit Parameters to Hyperspectral Data

DOE PAGES

McCann, Cooper; Repasky, Kevin S.; Morin, Mikindra; ...

2017-05-23

Hyperspectral image analysis has benefited from an array of methods that take advantage of the increased spectral depth compared to multispectral sensors; however, the focus of these developments has been on supervised classification methods. Lack of a priori knowledge regarding land cover characteristics can make unsupervised classification methods preferable under certain circumstances. An unsupervised classification technique is presented in this paper that utilizes physically relevant basis functions to model the reflectance spectra. These fit parameters used to generate the basis functions allow clustering based on spectral characteristics rather than spectral channels and provide both noise and data reduction. Histogram splittingmore » of the fit parameters is then used as a means of producing an unsupervised classification. Unlike current unsupervised classification techniques that rely primarily on Euclidian distance measures to determine similarity, the unsupervised classification technique uses the natural splitting of the fit parameters associated with the basis functions creating clusters that are similar in terms of physical parameters. The data set used in this work utilizes the publicly available data collected at Indian Pines, Indiana. This data set provides reference data allowing for comparisons of the efficacy of different unsupervised data analysis. The unsupervised histogram splitting technique presented in this paper is shown to be better than the standard unsupervised ISODATA clustering technique with an overall accuracy of 34.3/19.0% before merging and 40.9/39.2% after merging. Finally, this improvement is also seen as an improvement of kappa before/after merging of 24.8/30.5 for the histogram splitting technique compared to 15.8/28.5 for ISODATA.« less

Novel Histogram Based Unsupervised Classification Technique to Determine Natural Classes From Biophysically Relevant Fit Parameters to Hyperspectral Data

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

McCann, Cooper; Repasky, Kevin S.; Morin, Mikindra

Hyperspectral image analysis has benefited from an array of methods that take advantage of the increased spectral depth compared to multispectral sensors; however, the focus of these developments has been on supervised classification methods. Lack of a priori knowledge regarding land cover characteristics can make unsupervised classification methods preferable under certain circumstances. An unsupervised classification technique is presented in this paper that utilizes physically relevant basis functions to model the reflectance spectra. These fit parameters used to generate the basis functions allow clustering based on spectral characteristics rather than spectral channels and provide both noise and data reduction. Histogram splittingmore » of the fit parameters is then used as a means of producing an unsupervised classification. Unlike current unsupervised classification techniques that rely primarily on Euclidian distance measures to determine similarity, the unsupervised classification technique uses the natural splitting of the fit parameters associated with the basis functions creating clusters that are similar in terms of physical parameters. The data set used in this work utilizes the publicly available data collected at Indian Pines, Indiana. This data set provides reference data allowing for comparisons of the efficacy of different unsupervised data analysis. The unsupervised histogram splitting technique presented in this paper is shown to be better than the standard unsupervised ISODATA clustering technique with an overall accuracy of 34.3/19.0% before merging and 40.9/39.2% after merging. Finally, this improvement is also seen as an improvement of kappa before/after merging of 24.8/30.5 for the histogram splitting technique compared to 15.8/28.5 for ISODATA.« less

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.

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.

Breast density quantification with cone-beam CT: A post-mortem study

PubMed Central

Johnson, Travis; Ding, Huanjun; Le, Huy Q.; Ducote, Justin L.; Molloi, Sabee

2014-01-01

Forty post-mortem breasts were imaged with a flat-panel based cone-beam x-ray CT system at 50 kVp. The feasibility of breast density quantification has been investigated using standard histogram thresholding and an automatic segmentation method based on the fuzzy c-means algorithm (FCM). The breasts were chemically decomposed into water, lipid, and protein immediately after image acquisition was completed. The percent fibroglandular volume (%FGV) from chemical analysis was used as the gold standard for breast density comparison. Both image-based segmentation techniques showed good precision in breast density quantification with high linear coefficients between the right and left breast of each pair. When comparing with the gold standard using %FGV from chemical analysis, Pearson’s r-values were estimated to be 0.983 and 0.968 for the FCM clustering and the histogram thresholding techniques, respectively. The standard error of the estimate (SEE) was also reduced from 3.92% to 2.45% by applying the automatic clustering technique. The results of the postmortem study suggested that breast tissue can be characterized in terms of water, lipid and protein contents with high accuracy by using chemical analysis, which offers a gold standard for breast density studies comparing different techniques. In the investigated image segmentation techniques, the FCM algorithm had high precision and accuracy in breast density quantification. In comparison to conventional histogram thresholding, it was more efficient and reduced inter-observer variation. PMID:24254317

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.

Pretreatment ADC histogram analysis is a predictive imaging biomarker for bevacizumab treatment but not chemotherapy in recurrent glioblastoma.

PubMed

Ellingson, B M; Sahebjam, S; Kim, H J; Pope, W B; Harris, R J; Woodworth, D C; Lai, A; Nghiemphu, P L; Mason, W P; Cloughesy, T F

2014-04-01

Pre-treatment ADC characteristics have been shown to predict response to bevacizumab in recurrent glioblastoma multiforme. However, no studies have examined whether ADC characteristics are specific to this particular treatment. The purpose of the current study was to determine whether ADC histogram analysis is a bevacizumab-specific or treatment-independent biomarker of treatment response in recurrent glioblastoma multiforme. Eighty-nine bevacizumab-treated and 43 chemotherapy-treated recurrent glioblastoma multiformes never exposed to bevacizumab were included in this study. In all patients, ADC values in contrast-enhancing ROIs from MR imaging examinations performed at the time of recurrence, immediately before commencement of treatment for recurrence, were extracted and the resulting histogram was fitted to a mixed model with a double Gaussian distribution. Mean ADC in the lower Gaussian curve was used as the primary biomarker of interest. The Cox proportional hazards model and log-rank tests were used for survival analysis. Cox multivariate regression analysis accounting for the interaction between bevacizumab- and non-bevacizumab-treated patients suggested that the ability of the lower Gaussian curve to predict survival is dependent on treatment (progression-free survival, P = .045; overall survival, P = .003). Patients with bevacizumab-treated recurrent glioblastoma multiforme with a pretreatment lower Gaussian curve > 1.2 μm(2)/ms had a significantly longer progression-free survival and overall survival compared with bevacizumab-treated patients with a lower Gaussian curve < 1.2 μm(2)/ms. No differences in progression-free survival or overall survival were observed in the chemotherapy-treated cohort. Bevacizumab-treated patients with a mean lower Gaussian curve > 1.2 μm(2)/ms had a significantly longer progression-free survival and overall survival compared with chemotherapy-treated patients. The mean lower Gaussian curve from ADC histogram analysis is a predictive imaging biomarker for bevacizumab-treated, not chemotherapy-treated, recurrent glioblastoma multiforme. Patients with recurrent glioblastoma multiforme with a mean lower Gaussian curve > 1.2 μm(2)/ms have a survival advantage when treated with bevacizumab.

Differentiation of orbital lymphoma and idiopathic orbital inflammatory pseudotumor: combined diagnostic value of conventional MRI and histogram analysis of ADC maps.

PubMed

Ren, Jiliang; Yuan, Ying; Wu, Yingwei; Tao, Xiaofeng

2018-05-02

The overlap of morphological feature and mean ADC value restricted clinical application of MRI in the differential diagnosis of orbital lymphoma and idiopathic orbital inflammatory pseudotumor (IOIP). In this paper, we aimed to retrospectively evaluate the combined diagnostic value of conventional magnetic resonance imaging (MRI) and whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in the differentiation of the two lesions. In total, 18 patients with orbital lymphoma and 22 patients with IOIP were included, who underwent both conventional MRI and diffusion weighted imaging before treatment. Conventional MRI features and histogram parameters derived from ADC maps, including mean ADC (ADC mean ), median ADC (ADC median ), skewness, kurtosis, 10th, 25th, 75th and 90th percentiles of ADC (ADC 10 , ADC 25 , ADC 75 , ADC 90 ) were evaluated and compared between orbital lymphoma and IOIP. Multivariate logistic regression analysis was used to identify the most valuable variables for discriminating. Differential model was built upon the selected variables and receiver operating characteristic (ROC) analysis was also performed to determine the differential ability of the model. Multivariate logistic regression showed ADC 10 (P = 0.023) and involvement of orbit preseptal space (P = 0.029) were the most promising indexes in the discrimination of orbital lymphoma and IOIP. The logistic model defined by ADC 10 and involvement of orbit preseptal space was built, which achieved an AUC of 0.939, with sensitivity of 77.30% and specificity of 94.40%. Conventional MRI feature of involvement of orbit preseptal space and ADC histogram parameter of ADC 10 are valuable in differential diagnosis of orbital lymphoma and IOIP.

Incidence of chromosomal imbalances in advanced colorectal carcinomas and their metastases.

PubMed

Knösel, Thomas; Petersen, Simone; Schwabe, Holger; Schlüns, Karsten; Stein, Ulrike; Schlag, Peter Michael; Dietel, Manfred; Petersen, Iver

2002-02-01

Comparative genomic hybridization (CGH) was used to screen 54 advanced colon carcinomas. i.e., 24 primary tumors and 30 metastases, for chromosomal alterations. Using a sensitive statistical method for the determination of DNA imbalances and histograms for analysis of the incidence of changes, we identified the DNA over-representation of chromosome 20q as the most common alteration being present in 100% of cases. High incidence deletions were observed on 18q21-18q23 (96%), 4q27-4q28 (96%), 4p14 (87%), 5q21 (81%), 1p21-1p22 (72%), 21q21 (74%), 6q16 (72%), 3p12 (66%), 8p24-8p21 (66%), 9p21 (64%), 11q22 (64%), and 14q13-14q21 (64%). Further frequent over-representation was found on 7q12-7q11.2 (75%), 16p11-16p12 (70%), 19p13 (70%), 9q34 (67%), 19q13 (67%), 13q34 (64%), 13q13 (64%), 17q21 (59%), 22q11 (61%), 8q24 (57%), and 1q21 (57%). Pronounced DNA gains and losses being defined as regions in which the ratio profiles exceeded the values of 1.5 and 0.5, respectively, frequently colocalized with peaks of incidence curve. The use of difference histograms for the comparison of tumor subgroups as well as case-by-case histogram for the analysis of 15 paired tumor samples identified several of the above alterations as relevant for tumor progression and metastasis formation. The study identified additional loci and delineates more precisely those that have been previously reported. For comparative purposes, we have made our primary data (ratio profiles, clinicopathological parameters, histograms) available at the interactive web site http://amba.charite.de/cgh, where the incidence of changes can be determined at individual loci and additional parameters can be applied for the analysis of our CGH results.

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.

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.

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.

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.

Adaptive histogram equalization in digital radiography of destructive skeletal lesions.

PubMed

Braunstein, E M; Capek, P; Buckwalter, K; Bland, P; Meyer, C R

1988-03-01

Adaptive histogram equalization, an image-processing technique that distributes pixel values of an image uniformly throughout the gray scale, was applied to 28 plain radiographs of bone lesions, after they had been digitized. The non-equalized and equalized digital images were compared by two skeletal radiologists with respect to lesion margins, internal matrix, soft-tissue mass, cortical breakthrough, and periosteal reaction. Receiver operating characteristic (ROC) curves were constructed on the basis of the responses. Equalized images were superior to nonequalized images in determination of cortical breakthrough and presence or absence of periosteal reaction. ROC analysis showed no significant difference in determination of margins, matrix, or soft-tissue masses.

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.

Ultrasound texture analysis: Association with lymph node metastasis of papillary thyroid microcarcinoma.

PubMed

Kim, Soo-Yeon; Lee, Eunjung; Nam, Se Jin; Kim, Eun-Kyung; Moon, Hee Jung; Yoon, Jung Hyun; Han, Kyung Hwa; Kwak, Jin Young

2017-01-01

This retrospective study aimed to evaluate whether ultrasound texture analysis is useful to predict lymph node metastasis in patients with papillary thyroid microcarcinoma (PTMC). This study was approved by the Institutional Review Board, and the need to obtain informed consent was waived. Between May and July 2013, 361 patients (mean age, 43.8 ± 11.3 years; range, 16-72 years) who underwent staging ultrasound (US) and subsequent thyroidectomy for conventional PTMC ≤ 10 mm between May and July 2013 were included. Each PTMC was manually segmented and its histogram parameters (Mean, Standard deviation, Skewness, Kurtosis, and Entropy) were extracted with Matlab software. The mean values of histogram parameters and clinical and US features were compared according to lymph node metastasis using the independent t-test and Chi-square test. Multivariate logistic regression analysis was performed to identify the independent factors associated with lymph node metastasis. Tumors with lymph node metastasis (n = 117) had significantly higher entropy compared to those without lymph node metastasis (n = 244) (mean±standard deviation, 6.268±0.407 vs. 6.171±.0.405; P = .035). No additional histogram parameters showed differences in mean values according to lymph node metastasis. Entropy was not independently associated with lymph node metastasis on multivariate logistic regression analysis (Odds ratio, 0.977 [95% confidence interval (CI), 0.482-1.980]; P = .949). Younger age (Odds ratio, 0.962 [95% CI, 0.940-0.984]; P = .001) and lymph node metastasis on US (Odds ratio, 7.325 [95% CI, 3.573-15.020]; P < .001) were independently associated with lymph node metastasis. Texture analysis was not useful in predicting lymph node metastasis in patients with PTMC.

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

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.

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.

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

Assessing clutter reduction in parallel coordinates using image processing techniques

NASA Astrophysics Data System (ADS)

Alhamaydh, Heba; Alzoubi, Hussein; Almasaeid, Hisham

2018-01-01

Information visualization has appeared as an important research field for multidimensional data and correlation analysis in recent years. Parallel coordinates (PCs) are one of the popular techniques to visual high-dimensional data. A problem with the PCs technique is that it suffers from crowding, a clutter which hides important data and obfuscates the information. Earlier research has been conducted to reduce clutter without loss in data content. We introduce the use of image processing techniques as an approach for assessing the performance of clutter reduction techniques in PC. We use histogram analysis as our first measure, where the mean feature of the color histograms of the possible alternative orderings of coordinates for the PC images is calculated and compared. The second measure is the extracted contrast feature from the texture of PC images based on gray-level co-occurrence matrices. The results show that the best PC image is the one that has the minimal mean value of the color histogram feature and the maximal contrast value of the texture feature. In addition to its simplicity, the proposed assessment method has the advantage of objectively assessing alternative ordering of PC visualization.

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.

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.

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.

Dermal Structure in Lymphedema Patients with History of Acute Dermatolymphangioadenitis Evaluated by Histogram Analysis of Ultrasonography Findings: A Case-Control Study.

PubMed

Dai, Misako; Sato, Aya; Maeba, Hiroko; Iuchi, Terumi; Matsumoto, Masaru; Okuwa, Mayumi; Nakatani, Toshio; Sanada, Hiromi; Sugama, Junko

2016-03-01

Acute dermatolymphangioadenitis (ADLA) is a risk factor for increasing of edema and worsening severity. Reducing ADLA frequency is an important objective of lymphedema management because ADLA episodes are strongly associated with poor quality of life. Lymphedema changes dermal and subcutaneous structure, favoring ADLA; ADLA recurrence may be caused by structural change of the dermis. However, the structure of the skin following ADLA episodes has not been studied in depth. The aim of this study was to examine changes in the skin after episodes of ADLA in breast cancer-related lymphedema (BCRL) using histogram analysis of ultrasonography findings. This was a case-control study with matching for the duration of lymphedema. We compared 10 limbs (5 BCRL patients, Cases) with a history of ADLA and 14 limbs (7 BCRL patients, Controls) without. Ultrasonography was performed using a 20-MHz probe, and measurements were made at a site 10 cm proximal to the ulnar styloid process. We compared "skewness" of the images in the dermis from the histogram analysis. This study was approved by the Ethics Committee of Kanazawa University. Skewness was significantly different between the affected and unaffected limbs (p = 0.02). Cases showed a positive value (median 0.74, range -0.18 to 1.26), whereas Controls showed a negative value (median -0.21, range -0.45 to 0.31). Episodes of ADLA changed the distribution of echogenicity on imaging, which indicates a change in the collagen fibers in the dermis. These findings might contribute to improving the management of lymphedema and prevention of recurrent ADLA.

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.

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.

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 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.

Slope histogram distribution-based parametrisation of Martian geomorphic features

NASA Astrophysics Data System (ADS)

Balint, Zita; Székely, Balázs; Kovács, Gábor

2014-05-01

The application of geomorphometric methods on the large Martian digital topographic datasets paves the way to analyse the Martian areomorphic processes in more detail. One of the numerous methods is the analysis is to analyse local slope distributions. To this implementation a visualization program code was developed that allows to calculate the local slope histograms and to compare them based on Kolmogorov distance criterion. As input data we used the digital elevation models (DTMs) derived from HRSC high-resolution stereo camera image from various Martian regions. The Kolmogorov-criterion based discrimination produces classes of slope histograms that displayed using coloration obtaining an image map. In this image map the distribution can be visualized by their different colours representing the various classes. Our goal is to create a local slope histogram based classification for large Martian areas in order to obtain information about general morphological characteristics of the region. This is a contribution of the TMIS.ascrea project, financed by the Austrian Research Promotion Agency (FFG). The present research is partly realized in the frames of TÁMOP 4.2.4.A/2-11-1-2012-0001 high priority "National Excellence Program - Elaborating and Operating an Inland Student and Researcher Personal Support System convergence program" project's scholarship support, using Hungarian state and European Union funds and cofinances from the European Social Fund.

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.

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.

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

Performance analysis of a dual-tree algorithm for computing spatial distance histograms

PubMed Central

Chen, Shaoping; Tu, Yi-Cheng; Xia, Yuni

2011-01-01

Many scientific and engineering fields produce large volume of spatiotemporal data. The storage, retrieval, and analysis of such data impose great challenges to database systems design. Analysis of scientific spatiotemporal data often involves computing functions of all point-to-point interactions. One such analytics, the Spatial Distance Histogram (SDH), is of vital importance to scientific discovery. Recently, algorithms for efficient SDH processing in large-scale scientific databases have been proposed. These algorithms adopt a recursive tree-traversing strategy to process point-to-point distances in the visited tree nodes in batches, thus require less time when compared to the brute-force approach where all pairwise distances have to be computed. Despite the promising experimental results, the complexity of such algorithms has not been thoroughly studied. In this paper, we present an analysis of such algorithms based on a geometric modeling approach. The main technique is to transform the analysis of point counts into a problem of quantifying the area of regions where pairwise distances can be processed in batches by the algorithm. From the analysis, we conclude that the number of pairwise distances that are left to be processed decreases exponentially with more levels of the tree visited. This leads to the proof of a time complexity lower than the quadratic time needed for a brute-force algorithm and builds the foundation for a constant-time approximate algorithm. Our model is also general in that it works for a wide range of point spatial distributions, histogram types, and space-partitioning options in building the tree. PMID:21804753

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.

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.

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.

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

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.

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

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.

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.

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).

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.

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.

[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.

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.

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.

Quantitative evaluation of diffusion-kurtosis imaging for grading endometrial carcinoma: a comparative study with diffusion-weighted imaging.

PubMed

Chen, T; Li, Y; Lu, S-S; Zhang, Y-D; Wang, X-N; Luo, C-Y; Shi, H-B

2017-11-01

To evaluate the diagnostic performance of histogram analysis of diffusion kurtosis magnetic resonance imaging (DKI) and standard diffusion-weighted imaging (DWI) in discriminating tumour grades of endometrial carcinoma (EC). Seventy-three patients with EC were included in this study. The apparent diffusion coefficient (ADC) value from standard DWI, apparent diffusion for Gaussian distribution (D app ), and apparent kurtosis coefficient (K app ) from DKI were acquired using a 3 T magnetic resonance imaging (MRI) system. The measurement was based on an entire-tumour analysis. Histogram parameters (D app , K app , and ADC) were compared between high-grade (grade 3) and low-grade (grade 1 and 2) tumours. The diagnostic performance of imaging parameters for discriminating high- from low-grade tumours was analysed using a receiver operating characteristic curve (ROC). The area under the ROC curve (AUC) of the 10th percentile of D app , 90th percentile of K app and 10th percentile of ADC were higher than other parameters in distinguishing high-grade tumours from low-grade tumours (AUC=0.821, 0.891 and 0.801, respectively). The combination of 10th percentile of D app and 90th percentile of K app improved the AUC to 0.901, which was significantly higher than that of the 10th percentile of ADC (0.810, p=0.0314) in differentiating high- from low-grade EC. Entire-tumour volume histogram analysis of DKI and standard DWI were feasible for discriminating histological tumour grades of EC. DKI was relatively better than DWI in distinguishing high-grade from low-grade tumour in EC. Copyright © 2017. Published by Elsevier Ltd.

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.

Differentiating between Central Nervous System Lymphoma and High-grade Glioma Using Dynamic Susceptibility Contrast and Dynamic Contrast-enhanced MR Imaging with Histogram Analysis.

PubMed

Murayama, Kazuhiro; Nishiyama, Yuya; Hirose, Yuichi; Abe, Masato; Ohyu, Shigeharu; Ninomiya, Ayako; Fukuba, Takashi; Katada, Kazuhiro; Toyama, Hiroshi

2018-01-10

We evaluated the diagnostic performance of histogram analysis of data from a combination of dynamic susceptibility contrast (DSC)-MRI and dynamic contrast-enhanced (DCE)-MRI for quantitative differentiation between central nervous system lymphoma (CNSL) and high-grade glioma (HGG), with the aim of identifying useful perfusion parameters as objective radiological markers for differentiating between them. Eight lesions with CNSLs and 15 with HGGs who underwent MRI examination, including DCE and DSC-MRI, were enrolled in our retrospective study. DSC-MRI provides a corrected cerebral blood volume (cCBV), and DCE-MRI provides a volume transfer coefficient (K trans ) for transfer from plasma to the extravascular extracellular space. K trans and cCBV were measured from a round region-of-interest in the slice of maximum size on the contrast-enhanced lesion. The differences in t values between CNSL and HGG for determining the most appropriate percentile of K trans and cCBV were investigated. The differences in K trans , cCBV, and K trans /cCBV between CNSL and HGG were investigated using histogram analysis. Receiver operating characteristic (ROC) analysis of K trans , cCBV, and K trans /cCBV ratio was performed. The 30 th percentile (C30) in K trans and 80 th percentile (C80) in cCBV were the most appropriate percentiles for distinguishing between CNSL and HGG from the differences in t values. CNSL showed significantly lower C80 cCBV, significantly higher C30 K trans , and significantly higher C30 K trans /C80 cCBV than those of HGG. In ROC analysis, C30 K trans /C80 cCBV had the best discriminative value for differentiating between CNSL and HGG as compared to C30 K trans or C80 cCBV. The combination of K trans by DCE-MRI and cCBV by DSC-MRI was found to reveal the characteristics of vascularity and permeability of a lesion more precisely than either K trans or cCBV alone. Histogram analysis of these vascular microenvironments enabled quantitative differentiation between CNSL and HGG.

Frequency distribution histograms for the rapid analysis of data

NASA Technical Reports Server (NTRS)

Burke, P. V.; Bullen, B. L.; Poff, K. L.

1988-01-01

The mean and standard error are good representations for the response of a population to an experimental parameter and are frequently used for this purpose. Frequency distribution histograms show, in addition, responses of individuals in the population. Both the statistics and a visual display of the distribution of the responses can be obtained easily using a microcomputer and available programs. The type of distribution shown by the histogram may suggest different mechanisms to be tested.

Adaptive local thresholding for robust nucleus segmentation utilizing shape priors

NASA Astrophysics Data System (ADS)

Wang, Xiuzhong; Srinivas, Chukka

2016-03-01

This paper describes a novel local thresholding method for foreground detection. First, a Canny edge detection method is used for initial edge detection. Then, tensor voting is applied on the initial edge pixels, using a nonsymmetric tensor field tailored to encode prior information about nucleus size, shape, and intensity spatial distribution. Tensor analysis is then performed to generate the saliency image and, based on that, the refined edge. Next, the image domain is divided into blocks. In each block, at least one foreground and one background pixel are sampled for each refined edge pixel. The saliency weighted foreground histogram and background histogram are then created. These two histograms are used to calculate a threshold by minimizing the background and foreground pixel classification error. The block-wise thresholds are then used to generate the threshold for each pixel via interpolation. Finally, the foreground is obtained by comparing the original image with the threshold image. The effective use of prior information, combined with robust techniques, results in far more reliable foreground detection, which leads to robust nucleus segmentation.

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

Predicting the Valence of a Scene from Observers’ Eye Movements

PubMed Central

R.-Tavakoli, Hamed; Atyabi, Adham; Rantanen, Antti; Laukka, Seppo J.; Nefti-Meziani, Samia; Heikkilä, Janne

2015-01-01

Multimedia analysis benefits from understanding the emotional content of a scene in a variety of tasks such as video genre classification and content-based image retrieval. Recently, there has been an increasing interest in applying human bio-signals, particularly eye movements, to recognize the emotional gist of a scene such as its valence. In order to determine the emotional category of images using eye movements, the existing methods often learn a classifier using several features that are extracted from eye movements. Although it has been shown that eye movement is potentially useful for recognition of scene valence, the contribution of each feature is not well-studied. To address the issue, we study the contribution of features extracted from eye movements in the classification of images into pleasant, neutral, and unpleasant categories. We assess ten features and their fusion. The features are histogram of saccade orientation, histogram of saccade slope, histogram of saccade length, histogram of saccade duration, histogram of saccade velocity, histogram of fixation duration, fixation histogram, top-ten salient coordinates, and saliency map. We utilize machine learning approach to analyze the performance of features by learning a support vector machine and exploiting various feature fusion schemes. The experiments reveal that ‘saliency map’, ‘fixation histogram’, ‘histogram of fixation duration’, and ‘histogram of saccade slope’ are the most contributing features. The selected features signify the influence of fixation information and angular behavior of eye movements in the recognition of the valence of images. PMID:26407322

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.

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

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.

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.

Histogram analysis for smartphone-based rapid hematocrit determination

PubMed Central

Jalal, Uddin M.; Kim, Sang C.; Shim, Joon S.

2017-01-01

A novel and rapid analysis technique using histogram has been proposed for the colorimetric quantification of blood hematocrits. A smartphone-based “Histogram” app for the detection of hematocrits has been developed integrating the smartphone embedded camera with a microfluidic chip via a custom-made optical platform. The developed histogram analysis shows its effectiveness in the automatic detection of sample channel including auto-calibration and can analyze the single-channel as well as multi-channel images. Furthermore, the analyzing method is advantageous to the quantification of blood-hematocrit both in the equal and varying optical conditions. The rapid determination of blood hematocrits carries enormous information regarding physiological disorders, and the use of such reproducible, cost-effective, and standard techniques may effectively help with the diagnosis and prevention of a number of human diseases. PMID:28717569

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.

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.

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.

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.

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.

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).

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.

Non-invasive quantification of tumour heterogeneity in water diffusivity to differentiate malignant from benign tissues of urinary bladder: a phase I study.

PubMed

Nguyen, Huyen T; Shah, Zarine K; Mortazavi, Amir; Pohar, Kamal S; Wei, Lai; Jia, Guang; Zynger, Debra L; Knopp, Michael V

2017-05-01

To quantify the heterogeneity of the tumour apparent diffusion coefficient (ADC) using voxel-based analysis to differentiate malignancy from benign wall thickening of the urinary bladder. Nineteen patients with histopathological findings of their cystectomy specimen were included. A data set of voxel-based ADC values was acquired for each patient's lesion. Histogram analysis was performed on each data set to calculate uniformity (U) and entropy (E). The k-means clustering of the voxel-wised ADC data set was implemented to measure mean intra-cluster distance (MICD) and largest inter-cluster distance (LICD). Subsequently, U, E, MICD, and LICD for malignant tumours were compared with those for benign lesions using a two-sample t-test. Eleven patients had pathological confirmation of malignancy and eight with benign wall thickening. Histogram analysis showed that malignant tumours had a significantly higher degree of ADC heterogeneity with lower U (P = 0.016) and higher E (P = 0.005) than benign lesions. In agreement with these findings, k-means clustering of voxel-wise ADC indicated that bladder malignancy presented with significantly higher MICD (P < 0.001) and higher LICD (P = 0.002) than benign wall thickening. The quantitative assessment of tumour diffusion heterogeneity using voxel-based ADC analysis has the potential to become a non-invasive tool to distinguish malignant from benign tissues of urinary bladder cancer. • Heterogeneity is an intrinsic characteristic of tumoral tissue. • Non-invasive quantification of tumour heterogeneity can provide adjunctive information to improve cancer diagnosis accuracy. • Histogram analysis and k-means clustering can quantify tumour diffusion heterogeneity. • The quantification helps differentiate malignant from benign urinary bladder tissue.

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.

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

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.

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.

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.

Cluster analysis of quantitative parametric maps from DCE-MRI: application in evaluating heterogeneity of tumor response to antiangiogenic treatment.

PubMed

Longo, Dario Livio; Dastrù, Walter; Consolino, Lorena; Espak, Miklos; Arigoni, Maddalena; Cavallo, Federica; Aime, Silvio

2015-07-01

The objective of this study was to compare a clustering approach to conventional analysis methods for assessing changes in pharmacokinetic parameters obtained from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) during antiangiogenic treatment in a breast cancer model. BALB/c mice bearing established transplantable her2+ tumors were treated with a DNA-based antiangiogenic vaccine or with an empty plasmid (untreated group). DCE-MRI was carried out by administering a dose of 0.05 mmol/kg of Gadocoletic acid trisodium salt, a Gd-based blood pool contrast agent (CA) at 1T. Changes in pharmacokinetic estimates (K(trans) and vp) in a nine-day interval were compared between treated and untreated groups on a voxel-by-voxel analysis. The tumor response to therapy was assessed by a clustering approach and compared with conventional summary statistics, with sub-regions analysis and with histogram analysis. Both the K(trans) and vp estimates, following blood-pool CA injection, showed marked and spatial heterogeneous changes with antiangiogenic treatment. Averaged values for the whole tumor region, as well as from the rim/core sub-regions analysis were unable to assess the antiangiogenic response. Histogram analysis resulted in significant changes only in the vp estimates (p<0.05). The proposed clustering approach depicted marked changes in both the K(trans) and vp estimates, with significant spatial heterogeneity in vp maps in response to treatment (p<0.05), provided that DCE-MRI data are properly clustered in three or four sub-regions. This study demonstrated the value of cluster analysis applied to pharmacokinetic DCE-MRI parametric maps for assessing tumor response to antiangiogenic therapy. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

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.

A Bio Medical Waste Identification and Classification Algorithm Using Mltrp and Rvm.

PubMed

Achuthan, Aravindan; Ayyallu Madangopal, Vasumathi

2016-10-01

We aimed to extract the histogram features for text analysis and, to classify the types of Bio Medical Waste (BMW) for garbage disposal and management. The given BMW was preprocessed by using the median filtering technique that efficiently reduced the noise in the image. After that, the histogram features of the filtered image were extracted with the help of proposed Modified Local Tetra Pattern (MLTrP) technique. Finally, the Relevance Vector Machine (RVM) was used to classify the BMW into human body parts, plastics, cotton and liquids. The BMW image was collected from the garbage image dataset for analysis. The performance of the proposed BMW identification and classification system was evaluated in terms of sensitivity, specificity, classification rate and accuracy with the help of MATLAB. When compared to the existing techniques, the proposed techniques provided the better results. This work proposes a new texture analysis and classification technique for BMW management and disposal. It can be used in many real time applications such as hospital and healthcare management systems for proper BMW disposal.

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).

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.

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.

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

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.

Fast analysis of molecular dynamics trajectories with graphics processing units-Radial distribution function histogramming

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

Levine, Benjamin G., E-mail: ben.levine@temple.ed; Stone, John E., E-mail: johns@ks.uiuc.ed; Kohlmeyer, Axel, E-mail: akohlmey@temple.ed

2011-05-01

The calculation of radial distribution functions (RDFs) from molecular dynamics trajectory data is a common and computationally expensive analysis task. The rate limiting step in the calculation of the RDF is building a histogram of the distance between atom pairs in each trajectory frame. Here we present an implementation of this histogramming scheme for multiple graphics processing units (GPUs). The algorithm features a tiling scheme to maximize the reuse of data at the fastest levels of the GPU's memory hierarchy and dynamic load balancing to allow high performance on heterogeneous configurations of GPUs. Several versions of the RDF algorithm aremore » presented, utilizing the specific hardware features found on different generations of GPUs. We take advantage of larger shared memory and atomic memory operations available on state-of-the-art GPUs to accelerate the code significantly. The use of atomic memory operations allows the fast, limited-capacity on-chip memory to be used much more efficiently, resulting in a fivefold increase in performance compared to the version of the algorithm without atomic operations. The ultimate version of the algorithm running in parallel on four NVIDIA GeForce GTX 480 (Fermi) GPUs was found to be 92 times faster than a multithreaded implementation running on an Intel Xeon 5550 CPU. On this multi-GPU hardware, the RDF between two selections of 1,000,000 atoms each can be calculated in 26.9 s per frame. The multi-GPU RDF algorithms described here are implemented in VMD, a widely used and freely available software package for molecular dynamics visualization and analysis.« less

Fast Analysis of Molecular Dynamics Trajectories with Graphics Processing Units—Radial Distribution Function Histogramming

PubMed Central

Stone, John E.; Kohlmeyer, Axel

2011-01-01

The calculation of radial distribution functions (RDFs) from molecular dynamics trajectory data is a common and computationally expensive analysis task. The rate limiting step in the calculation of the RDF is building a histogram of the distance between atom pairs in each trajectory frame. Here we present an implementation of this histogramming scheme for multiple graphics processing units (GPUs). The algorithm features a tiling scheme to maximize the reuse of data at the fastest levels of the GPU’s memory hierarchy and dynamic load balancing to allow high performance on heterogeneous configurations of GPUs. Several versions of the RDF algorithm are presented, utilizing the specific hardware features found on different generations of GPUs. We take advantage of larger shared memory and atomic memory operations available on state-of-the-art GPUs to accelerate the code significantly. The use of atomic memory operations allows the fast, limited-capacity on-chip memory to be used much more efficiently, resulting in a fivefold increase in performance compared to the version of the algorithm without atomic operations. The ultimate version of the algorithm running in parallel on four NVIDIA GeForce GTX 480 (Fermi) GPUs was found to be 92 times faster than a multithreaded implementation running on an Intel Xeon 5550 CPU. On this multi-GPU hardware, the RDF between two selections of 1,000,000 atoms each can be calculated in 26.9 seconds per frame. The multi-GPU RDF algorithms described here are implemented in VMD, a widely used and freely available software package for molecular dynamics visualization and analysis. PMID:21547007

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.

Application of Markov Models for Analysis of Development of Psychological Characteristics

ERIC Educational Resources Information Center

Kuravsky, Lev S.; Malykh, Sergey B.

2004-01-01

A technique to study combined influence of environmental and genetic factors on the base of changes in phenotype distributions is presented. Histograms are exploited as base analyzed characteristics. A continuous time, discrete state Markov process with piece-wise constant interstate transition rates is associated with evolution of each histogram.…

[Comparison of film-screen combinations in contrast-detail diagram and with interactive image analysis. 3: Trimodal histograms of gray scale distribution in bar groups of lead pattern images].

PubMed

Hagemann, G; Eichbaum, G; Stamm, G

1998-05-01

The following four screen film combinations were compared: a) a combination of anticrossover film and UV-light emitting screens, b) a combination of blue-light emitting screens and film and c) two conventional green fluorescing screen film combinations. Radiographs of a specially designed plexiglass phantom (0.2 x 0.2 x 0.12 m3) with bar patterns of lead and plaster and of air, respectively were obtained using the following parameters: 12 pulse generator, 0.6 mm focus size, 4.7 mm aluminum prefilter, a grid with 40 lines/cm (12:1) and a focus-detector distance of 1.15 m. Image analysis was performed using an Ibas system and a Zeiss Kontron computer. Display conditions were the following: display distance 0.12 m, a vario film objective 35/70 (Zeiss), a video camera tube with a PbO photocathode, 625 lines (Siemens Heimann), an Ibas image matrix of 512 x 512 pixels with a spatial resolution of ca. 7 cycles/mm, the projected matrix area was 5000 micron 2. Maxima in the histograms of a grouped bar pattern were estimated as mean values from the bar and gap regions ("mean value method"). They were used to calculate signal contrast, standard deviations of the means and scatter fraction. Comparing the histograms with respect to spatial resolution and kV setting a clear advantage of the UVR system becomes obvious. The quantitative analysis yielded a maximum spatial resolution of approx. 3 cycles/mm for the UVR system at 60 kV which decreased to half of this value at 117 kV caused by the increasing influence of scattered radiation. A ranking of screen-film systems with respect to image quality and dose requirement is presented. For its evaluation an interactive image analysis using the mean value method was found to be superior to signal/noise ratio measurements and visual analysis in respect to diagnostic relevance and saving of time.

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.

Clinical outcomes using carbon-ion radiotherapy and dose-volume histogram comparison between carbon-ion radiotherapy and photon therapy for T2b-4N0M0 non-small cell lung cancer-A pilot study.

PubMed

Shirai, Katsuyuki; Kawashima, Motohiro; Saitoh, Jun-Ichi; Abe, Takanori; Fukata, Kyohei; Shigeta, Yuka; Irie, Daisuke; Shiba, Shintaro; Okano, Naoko; Ohno, Tatsuya; Nakano, Takashi

2017-01-01

The safety and efficacy of carbon-ion radiotherapy for advanced non-small cell lung cancer have not been established. We evaluated the clinical outcomes and dose-volume histogram parameters of carbon-ion radiotherapy compared with photon therapy in T2b-4N0M0 non-small cell lung cancer. Twenty-three patients were treated with carbon-ion radiotherapy between May 2011 and December 2015. Seven, 14, and 2 patients had T2b, T3, and T4, respectively. The median age was 78 (range, 53-91) years, with 22 male patients. There were 12 adenocarcinomas, 8 squamous cell carcinomas, 1 non-small cell lung carcinoma, and 2 clinically diagnosed lung cancers. Eleven patients were operable, and 12 patients were inoperable. Most patients (91%) were treated with carbon-ion radiotherapy of 60.0 Gy relative biological effectiveness (RBE) in 4 fractions or 64.0 Gy (RBE) in 16 fractions. Local control and overall survival rates were calculated. Dose-volume histogram parameters of normal lung and tumor coverages were compared between carbon-ion radiotherapy and photon therapies, including three-dimensional conformal radiotherapy (3DCRT) and intensity-modulated radiotherapy (IMRT). The median follow-up of surviving patients was 25 months. Three patients experienced local recurrence, and the 2-year local control rate was 81%. During follow-up, 5 patients died of lung cancer, and 1 died of intercurrent disease. The 2-year overall survival rate was 70%. Operable patients had a better overall survival rate compared with inoperable patients (100% vs. 43%; P = 0.04). There was no grade ≥2 radiation pneumonitis. In dose-volume histogram analysis, carbon-ion radiotherapy had a significantly lower dose to normal lung and greater tumor coverage compared with photon therapies. Carbon-ion radiotherapy was effectively and safely performed for T2b-4N0M0 non-small cell lung cancer, and the dose distribution was superior compared with those for photon therapies. A Japanese multi-institutional study is ongoing to prospectively evaluate these patients and establish the use of carbon-ion radiotherapy.

Carbon Nanostructure Examined by Lattice Fringe Analysis of High Resolution Transmission Electron Microscopy Images

NASA Technical Reports Server (NTRS)

VanderWal, Randy L.; Tomasek, Aaron J.; Street, Kenneth; Thompson, William K.

2002-01-01

The dimensions of graphitic layer planes directly affect the reactivity of soot towards oxidation and growth. Quantification of graphitic structure could be used to develop and test correlations between the soot nanostructure and its reactivity. Based upon transmission electron microscopy images, this paper provides a demonstration of the robustness of a fringe image analysis code for determining the level of graphitic structure within nanoscale carbon, i.e. soot. Results, in the form of histograms of graphitic layer plane lengths, are compared to their determination through Raman analysis.

Carbon Nanostructure Examined by Lattice Fringe Analysis of High Resolution Transmission Electron Microscopy Images

NASA Technical Reports Server (NTRS)

VanderWal, Randy L.; Tomasek, Aaron J.; Street, Kenneth; Thompson, William K.; Hull, David R.

2003-01-01

The dimensions of graphitic layer planes directly affect the reactivity of soot towards oxidation and growth. Quantification of graphitic structure could be used to develop and test correlations between the soot nanostructure and its reactivity. Based upon transmission electron microscopy images, this paper provides a demonstration of the robustness of a fringe image analysis code for determining the level of graphitic structure within nanoscale carbon, i.e., soot. Results, in the form of histograms of graphitic layer plane lengths, are compared to their determination through Raman analysis.

Multicenter study of quantitative computed tomography analysis using a computer-aided three-dimensional system in patients with idiopathic pulmonary fibrosis.

PubMed

Iwasawa, Tae; Kanauchi, Tetsu; Hoshi, Toshiko; Ogura, Takashi; Baba, Tomohisa; Gotoh, Toshiyuki; Oba, Mari S

2016-01-01

To evaluate the feasibility of automated quantitative analysis with a three-dimensional (3D) computer-aided system (i.e., Gaussian histogram normalized correlation, GHNC) of computed tomography (CT) images from different scanners. Each institution's review board approved the research protocol. Informed patient consent was not required. The participants in this multicenter prospective study were 80 patients (65 men, 15 women) with idiopathic pulmonary fibrosis. Their mean age was 70.6 years. Computed tomography (CT) images were obtained by four different scanners set at different exposures. We measured the extent of fibrosis using GHNC, and used Pearson's correlation analysis, Bland-Altman plots, and kappa analysis to directly compare the GHNC results with manual scoring by radiologists. Multiple linear regression analysis was performed to determine the association between the CT data and forced vital capacity (FVC). For each scanner, the extent of fibrosis as determined by GHNC was significantly correlated with the radiologists' score. In multivariate analysis, the extent of fibrosis as determined by GHNC was significantly correlated with FVC (p < 0.001). There was no significant difference between the results obtained using different CT scanners. Gaussian histogram normalized correlation was feasible, irrespective of the type of CT scanner used.

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

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

PubMed

Tam, Allison; Barker, Jocelyn; Rubin, Daniel

2016-01-01

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

MTR and In-vivo 1H-MRS studies on mouse brain with parkinson's disease

NASA Astrophysics Data System (ADS)

Yoon, Moon-Hyun; Kim, Hyeon-Jin; Chung, Jin-Yeung; Doo, Ah-Reum; Park, Hi-Joon; Kim, Seung-Nam; Choe, Bo-Young

2012-12-01

The aim of this study was to investigate whether the changes in the magnetization transfer ratio (MTR) histogram are related to specific characteristics of Parkinson's disease (PD) and to investigate whether the MTR histogram parameters are associated with neurochemical dysfunction by performing in vivo proton magnetic resonance spectroscopy (1H-MRS). MTR and in vivo 1H-MRS studies were performed on control mice (n = 10) and 1-methyl-1,2,3,6-tetrahydropyridine intoxicated mice (n = 10). All the MTR and in vivo 1H-MRS experiments were performed on a 9.4 T MRI/MRS system (Bruker Biospin, Germany) using a standard head coil. The protondensity fast spin echo (FSE) images and the T2-weighted spin echo (SE) images were acquired with no gap. Outer volume suppression (OVS), combined with the ultra-short echo-time stimulated echo acquisition mode (STEAM), was used for the localized in-vivo 1H-MRS. The quantitative analysis of metabolites was performed from the 1H spectra obtained in vivo on the striatum (ST) by using jMRUI (Lyon, France). The peak height of the MTR histograms in the PD model group was significantly lower than that in the control group (p < 0.05). The midbrain MTR values for volume were lower in the PD group than the control group(p < 0.05). The complex peak (Glx: glutamine+glutamate+ GABA)/creatine (Cr) ratio of the right ST in the PD group was significantly increased as compared to that of the control group. The present study revealed that the peak height of the MTR histogram was significantly decreased in the ST and substantia nigra, and a significant increase in the Gl x /Cr ratio was found in the ST of the PD group, as compared with that of the control group. These findings could reflect the early phase of neuronal dysfunction of neurotransmitters.

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.

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.

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…

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.

Selecting a Variable for Predicting the Diagnosis of PTB Patients From Comparison of Chest X-ray Images

NASA Astrophysics Data System (ADS)

Mohd. Rijal, Omar; Mohd. Noor, Norliza; Teng, Shee Lee

A statistical method of comparing two digital chest radiographs for Pulmonary Tuberculosis (PTB) patients has been proposed. After applying appropriate image registration procedures, a selected subset of each image is converted to an image histogram (or box plot). Comparing two chest X-ray images is equivalent to the direct comparison of the two corresponding histograms. From each histogram, eleven percentiles (of image intensity) are calculated. The number of percentiles that shift to the left (NLSP) when second image is compared to the first has been shown to be an indicator of patients` progress. In this study, the values of NLSP is to be compared with the actual diagnosis (Y) of several medical practitioners. A logistic regression model is used to study the relationship between NLSP and Y. This study showed that NLSP may be used as an alternative or second opinion for Y. The proposed regression model also show that important explanatory variables such as outcomes of sputum test (Z) and degree of image registration (W) may be omitted when estimating Y-values.

ATLAS offline data quality monitoring

NASA Astrophysics Data System (ADS)

Adelman, J.; Baak, M.; Boelaert, N.; D'Onofrio, M.; Frost, J. A.; Guyot, C.; Hauschild, M.; Hoecker, A.; Leney, K. J. C.; Lytken, E.; Martinez-Perez, M.; Masik, J.; Nairz, A. M.; Onyisi, P. U. E.; Roe, S.; Schaetzel, S.; Wilson, M. G.

2010-04-01

The ATLAS experiment at the Large Hadron Collider reads out 100 Million electronic channels at a rate of 200 Hz. Before the data are shipped to storage and analysis centres across the world, they have to be checked to be free from irregularities which render them scientifically useless. Data quality offline monitoring provides prompt feedback from full first-pass event reconstruction at the Tier-0 computing centre and can unveil problems in the detector hardware and in the data processing chain. Detector information and reconstructed proton-proton collision event characteristics are distilled into a few key histograms and numbers which are automatically compared with a reference. The results of the comparisons are saved as status flags in a database and are published together with the histograms on a web server. They are inspected by a 24/7 shift crew who can notify on-call experts in case of problems and in extreme cases signal data taking abort.

Mesoscale analysis of failure in quasi-brittle materials: comparison between lattice model and acoustic emission data.

PubMed

Grégoire, David; Verdon, Laura; Lefort, Vincent; Grassl, Peter; Saliba, Jacqueline; Regoin, Jean-Pierre; Loukili, Ahmed; Pijaudier-Cabot, Gilles

2015-10-25

The purpose of this paper is to analyse the development and the evolution of the fracture process zone during fracture and damage in quasi-brittle materials. A model taking into account the material details at the mesoscale is used to describe the failure process at the scale of the heterogeneities. This model is used to compute histograms of the relative distances between damaged points. These numerical results are compared with experimental data, where the damage evolution is monitored using acoustic emissions. Histograms of the relative distances between damage events in the numerical calculations and acoustic events in the experiments exhibit good agreement. It is shown that the mesoscale model provides relevant information from the point of view of both global responses and the local failure process. © 2015 The Authors. International Journal for Numerical and Analytical Methods in Geomechanics published by John Wiley & Sons Ltd.

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.

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.

Extracting rate coefficients from single-molecule photon trajectories and FRET efficiency histograms for a fast-folding protein.

PubMed

Chung, Hoi Sung; Gopich, Irina V; McHale, Kevin; Cellmer, Troy; Louis, John M; Eaton, William A

2011-04-28

Recently developed statistical methods by Gopich and Szabo were used to extract folding and unfolding rate coefficients from single-molecule Förster resonance energy transfer (FRET) data for proteins with kinetics too fast to measure waiting time distributions. Two types of experiments and two different analyses were performed. In one experiment bursts of photons were collected from donor and acceptor fluorophores attached to a 73-residue protein, α(3)D, freely diffusing through the illuminated volume of a confocal microscope system. In the second, the protein was immobilized by linkage to a surface, and photons were collected until one of the fluorophores bleached. Folding and unfolding rate coefficients and mean FRET efficiencies for the folded and unfolded subpopulations were obtained from a photon by photon analysis of the trajectories using a maximum likelihood method. The ability of the method to describe the data in terms of a two-state model was checked by recoloring the photon trajectories with the extracted parameters and comparing the calculated FRET efficiency histograms with the measured histograms. The sum of the rate coefficients for the two-state model agreed to within 30% with the relaxation rate obtained from the decay of the donor-acceptor cross-correlation function, confirming the high accuracy of the method. Interestingly, apparently reliable rate coefficients could be extracted using the maximum likelihood method, even at low (<10%) population of the minor component where the cross-correlation function was too noisy to obtain any useful information. The rate coefficients and mean FRET efficiencies were also obtained in an approximate procedure by simply fitting the FRET efficiency histograms, calculated by binning the donor and acceptor photons, with a sum of three-Gaussian functions. The kinetics are exposed in these histograms by the growth of a FRET efficiency peak at values intermediate between the folded and unfolded peaks as the bin size increases, a phenomenon with similarities to NMR exchange broadening. When comparable populations of folded and unfolded molecules are present, this method yields rate coefficients in very good agreement with those obtained with the maximum likelihood method. As a first step toward characterizing transition paths, the Viterbi algorithm was used to locate the most probable transition points in the photon trajectories.

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…

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.

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

Particle size analysis of some water/oil/water multiple emulsions.

PubMed

Ursica, L; Tita, D; Palici, I; Tita, B; Vlaia, V

2005-04-29

Particle size analysis gives useful information about the structure and stability of multiple emulsions, which are important characteristics of these systems. It also enables the observation of the growth process of particles dispersed in multiple emulsions, accordingly, the evolution of their dimension in time. The size of multiple particles in the seven water/oil/water (W/O/W) emulsions was determined by measuring the particles size observed during the microscopic examination. In order to describe the distribution of the size of multiple particles, the value of two parameters that define the particle size was calculated: the arithmetical mean diameter and the median diameter. The results of the particle size analysis in the seven multiple emulsions W/O/W studied are presented as histograms of the distribution density immediately, 1 and 3 months after the preparation of each emulsion, as well as by establishing the mean and the median diameter of particles. The comparative study of the distribution histograms and of the mean and median diameters of W/O/W multiple particles indicates that the prepared emulsions are fine and very fine dispersions, stable, and presenting a growth of the abovementioned diameters during the study.

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.

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.

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.

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.

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.

Design of a Borescope for Extravehicular Non-Destructive Applications

NASA Technical Reports Server (NTRS)

Bachnak, Rafic

2003-01-01

Anomalies such as corrosion, structural damage, misalignment, cracking, stress fiactures, pitting, or wear can be detected and monitored by the aid of a borescope. A borescope requires a source of light for proper operation. Today s current lighting technology market consists of incandescent lamps, fluorescent lamps and other types of electric arc and electric discharge vapor lamp. Recent advances in LED technology have made LEDs viable for a number of applications, including vehicle stoplights, traffic lights, machine-vision-inspection, illumination, and street signs. LEDs promise significant reduction in power consumption compared to other sources of light. This project focused on comparing images taken by the Olympus IPLEX, using two different light sources. One of the sources is the 50-W internal metal halide lamp and the other is a 1 W LED placed at the tip of the insertion tube. Images acquired using these two light sources were quantitatively compared using their histogram, intensity profile along a line segment, and edge detection. Also, images were qualitatively compared using image registration and transformation [l]. The gray-level histogram, edge detection, image profile and image registration do not offer conclusive results. The LED light source, however, produces good images for visual inspection by an operator. Analysis using pattern recognition using Eigenfaces and Gaussian Pyramid in face recognition may be more useful.

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

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

Tam, Allison; Barker, Jocelyn; Rubin, Daniel

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

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.

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.

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.

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.

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.

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.

Rocketdyne automated dynamics data analysis and management system

NASA Technical Reports Server (NTRS)

Tarn, Robert B.

1988-01-01

An automated dynamics data analysis and management systems implemented on a DEC VAX minicomputer cluster is described. Multichannel acquisition, Fast Fourier Transformation analysis, and an online database have significantly improved the analysis of wideband transducer responses from Space Shuttle Main Engine testing. Leakage error correction to recover sinusoid amplitudes and correct for frequency slewing is described. The phase errors caused by FM recorder/playback head misalignment are automatically measured and used to correct the data. Data compression methods are described and compared. The system hardware is described. Applications using the data base are introduced, including software for power spectral density, instantaneous time history, amplitude histogram, fatigue analysis, and rotordynamics expert system analysis.

[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.

Idiopathic Pulmonary Fibrosis: Data-driven Textural Analysis of Extent of Fibrosis at Baseline and 15-Month Follow-up.

PubMed

Humphries, Stephen M; Yagihashi, Kunihiro; Huckleberry, Jason; Rho, Byung-Hak; Schroeder, Joyce D; Strand, Matthew; Schwarz, Marvin I; Flaherty, Kevin R; Kazerooni, Ella A; van Beek, Edwin J R; Lynch, David A

2017-10-01

Purpose To evaluate associations between pulmonary function and both quantitative analysis and visual assessment of thin-section computed tomography (CT) images at baseline and at 15-month follow-up in subjects with idiopathic pulmonary fibrosis (IPF). Materials and Methods This retrospective analysis of preexisting anonymized data, collected prospectively between 2007 and 2013 in a HIPAA-compliant study, was exempt from additional institutional review board approval. The extent of lung fibrosis at baseline inspiratory chest CT in 280 subjects enrolled in the IPF Network was evaluated. Visual analysis was performed by using a semiquantitative scoring system. Computer-based quantitative analysis included CT histogram-based measurements and a data-driven textural analysis (DTA). Follow-up CT images in 72 of these subjects were also analyzed. Univariate comparisons were performed by using Spearman rank correlation. Multivariate and longitudinal analyses were performed by using a linear mixed model approach, in which models were compared by using asymptotic χ 2 tests. Results At baseline, all CT-derived measures showed moderate significant correlation (P < .001) with pulmonary function. At follow-up CT, changes in DTA scores showed significant correlation with changes in both forced vital capacity percentage predicted (ρ = -0.41, P < .001) and diffusing capacity for carbon monoxide percentage predicted (ρ = -0.40, P < .001). Asymptotic χ 2 tests showed that inclusion of DTA score significantly improved fit of both baseline and longitudinal linear mixed models in the prediction of pulmonary function (P < .001 for both). Conclusion When compared with semiquantitative visual assessment and CT histogram-based measurements, DTA score provides additional information that can be used to predict diminished function. Automatic quantification of lung fibrosis at CT yields an index of severity that correlates with visual assessment and functional change in subjects with IPF. © RSNA, 2017.

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

[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.

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.

Quantitative characterization of brain β-amyloid in 718 normal subjects using a joint PiB/FDG PET image histogram

NASA Astrophysics Data System (ADS)

Camp, Jon J.; Hanson, Dennis P.; Lowe, Val J.; Kemp, Bradley J.; Senjem, Matthew L.; Murray, Melissa E.; Dickson, Dennis W.; Parisi, Joseph E.; Petersen, Ronald C.; Robb, Richard A.; Holmes, David R.

2016-03-01

We have previously described an automated system for the co-registration of PiB and FDG PET images with structural MRI and a neurological anatomy atlas to produce region-specific quantization of cortical activity and amyloid burden. We also reported a global joint PiB/FDG histogram-based measure (FDG-Associated PiB Uptake Ratio - FAPUR) that performed as well as regional PiB ratio in stratifying Alzheimer's disease (AD) and Lewy Body Dementia (LBD) patients from normal subjects in an autopsy-verified cohort of 31. In this paper we examine results of this analysis on a clinically-verified cohort of 718 normal volunteers. We found that the global FDG ratio correlated negatively with age (r2 = 0.044) and global PiB ratio correlated positively with age (r2=0.038). FAPUR also correlated negatively with age (r2-.025), and in addition, we introduce a new metric - the Pearson's correlation coefficient (r2) of the joint PiB/FDG histogram which correlates positively (r2=0.014) with age. We then used these measurements to construct age-weighted Z-scores for all measurements made on the original autopsy cohort. We found similar stratification using Z-scores compared to raw values; however, the joint PiB/FDG r2 Z-score showed the greatest stratification ability.

Characterization of Diffusion Metric Map Similarity in Data From a Clinical Data Repository Using Histogram Distances

PubMed Central

Warner, Graham C.; Helmer, Karl G.

2018-01-01

As the sharing of data is mandated by funding agencies and journals, reuse of data has become more prevalent. It becomes imperative, therefore, to develop methods to characterize the similarity of data. While users can group data based on the acquisition parameters stored in the file headers, these gives no indication whether a file can be combined with other data without increasing the variance in the data set. Methods have been implemented that characterize the signal-to-noise ratio or identify signal drop-outs in the raw image files, but potential users of data often have access to calculated metric maps and these are more difficult to characterize and compare. Here we describe a histogram-distance-based method applied to diffusion metric maps of fractional anisotropy and mean diffusivity that were generated using data extracted from a repository of clinically-acquired MRI data. We describe the generation of the data set, the pitfalls specific to diffusion MRI data, and the results of the histogram distance analysis. We find that, in general, data from GE scanners are less similar than are data from Siemens scanners. We also find that the distribution of distance metric values is not Gaussian at any selection of the acquisition parameters considered here (field strength, number of gradient directions, b-value, and vendor). PMID:29568257

Ocean Wave Slope Statistics from Automated Analysis of Sun Glitter Photographs

DTIC Science & Technology

1985-06-01

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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.

A New Pivoting and Iterative Text Detection Algorithm for Biomedical Images

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

Xu, Songhua; Krauthammer, Prof. Michael

2010-01-01

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

Face-iris multimodal biometric scheme based on feature level fusion

NASA Astrophysics Data System (ADS)

Huo, Guang; Liu, Yuanning; Zhu, Xiaodong; Dong, Hongxing; He, Fei

2015-11-01

Unlike score level fusion, feature level fusion demands all the features extracted from unimodal traits with high distinguishability, as well as homogeneity and compatibility, which is difficult to achieve. Therefore, most multimodal biometric research focuses on score level fusion, whereas few investigate feature level fusion. We propose a face-iris recognition method based on feature level fusion. We build a special two-dimensional-Gabor filter bank to extract local texture features from face and iris images, and then transform them by histogram statistics into an energy-orientation variance histogram feature with lower dimensions and higher distinguishability. Finally, through a fusion-recognition strategy based on principal components analysis and support vector machine (FRSPS), feature level fusion and one-to-n identification are accomplished. The experimental results demonstrate that this method can not only effectively extract face and iris features but also provide higher recognition accuracy. Compared with some state-of-the-art fusion methods, the proposed method has a significant performance advantage.

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.

A New Pivoting and Iterative Text Detection Algorithm for Biomedical Images

PubMed Central

Xu, Songhua; Krauthammer, Michael

2010-01-01

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

Dynamic Histogram Analysis To Determine Free Energies and Rates from Biased Simulations.

PubMed

Stelzl, Lukas S; Kells, Adam; Rosta, Edina; Hummer, Gerhard

2017-12-12

We present an algorithm to calculate free energies and rates from molecular simulations on biased potential energy surfaces. As input, it uses the accumulated times spent in each state or bin of a histogram and counts of transitions between them. Optimal unbiased equilibrium free energies for each of the states/bins are then obtained by maximizing the likelihood of a master equation (i.e., first-order kinetic rate model). The resulting free energies also determine the optimal rate coefficients for transitions between the states or bins on the biased potentials. Unbiased rates can be estimated, e.g., by imposing a linear free energy condition in the likelihood maximization. The resulting "dynamic histogram analysis method extended to detailed balance" (DHAMed) builds on the DHAM method. It is also closely related to the transition-based reweighting analysis method (TRAM) and the discrete TRAM (dTRAM). However, in the continuous-time formulation of DHAMed, the detailed balance constraints are more easily accounted for, resulting in compact expressions amenable to efficient numerical treatment. DHAMed produces accurate free energies in cases where the common weighted-histogram analysis method (WHAM) for umbrella sampling fails because of slow dynamics within the windows. Even in the limit of completely uncorrelated data, where WHAM is optimal in the maximum-likelihood sense, DHAMed results are nearly indistinguishable. We illustrate DHAMed with applications to ion channel conduction, RNA duplex formation, α-helix folding, and rate calculations from accelerated molecular dynamics. DHAMed can also be used to construct Markov state models from biased or replica-exchange molecular dynamics simulations. By using binless WHAM formulated as a numerical minimization problem, the bias factors for the individual states can be determined efficiently in a preprocessing step and, if needed, optimized globally afterward.

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

Preliminary evaluation of a fully automated quantitative framework for characterizing general breast tissue histology via color histogram and color texture analysis

NASA Astrophysics Data System (ADS)

Keller, Brad M.; Gastounioti, Aimilia; Batiste, Rebecca C.; Kontos, Despina; Feldman, Michael D.

2016-03-01

Visual characterization of histologic specimens is known to suffer from intra- and inter-observer variability. To help address this, we developed an automated framework for characterizing digitized histology specimens based on a novel application of color histogram and color texture analysis. We perform a preliminary evaluation of this framework using a set of 73 trichrome-stained, digitized slides of normal breast tissue which were visually assessed by an expert pathologist in terms of the percentage of collagenous stroma, stromal collagen density, duct-lobular unit density and the presence of elastosis. For each slide, our algorithm automatically segments the tissue region based on the lightness channel in CIELAB colorspace. Within each tissue region, a color histogram feature vector is extracted using a common color palette for trichrome images generated with a previously described method. Then, using a whole-slide, lattice-based methodology, color texture maps are generated using a set of color co-occurrence matrix statistics: contrast, correlation, energy and homogeneity. The extracted features sets are compared to the visually assessed tissue characteristics. Overall, the extracted texture features have high correlations to both the percentage of collagenous stroma (r=0.95, p<0.001) and duct-lobular unit density (r=0.71, p<0.001) seen in the tissue samples, and several individual features were associated with either collagen density and/or the presence of elastosis (p<=0.05). This suggests that the proposed framework has promise as a means to quantitatively extract descriptors reflecting tissue-level characteristics and thus could be useful in detecting and characterizing histological processes in digitized histology specimens.

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

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

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.

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.

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

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

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.

Texton-based analysis of paintings

NASA Astrophysics Data System (ADS)

van der Maaten, Laurens J. P.; Postma, Eric O.

2010-08-01

The visual examination of paintings is traditionally performed by skilled art historians using their eyes. Recent advances in intelligent systems may support art historians in determining the authenticity or date of creation of paintings. In this paper, we propose a technique for the examination of brushstroke structure that views the wildly overlapping brushstrokes as texture. The analysis of the painting texture is performed with the help of a texton codebook, i.e., a codebook of small prototypical textural patches. The texton codebook can be learned from a collection of paintings. Our textural analysis technique represents paintings in terms of histograms that measure the frequency by which the textons in the codebook occur in the painting (so-called texton histograms). We present experiments that show the validity and effectiveness of our technique for textural analysis on a collection of digitized high-resolution reproductions of paintings by Van Gogh and his contemporaries. As texton histograms cannot be easily be interpreted by art experts, the paper proposes to approaches to visualize the results on the textural analysis. The first approach visualizes the similarities between the histogram representations of paintings by employing a recently proposed dimensionality reduction technique, called t-SNE. We show that t-SNE reveals a clear separation of paintings created by Van Gogh and those created by other painters. In addition, the period of creation is faithfully reflected in the t-SNE visualizations. The second approach visualizes the similarities and differences between paintings by highlighting regions in a painting in which the textural structure of the painting is unusual. We illustrate the validity of this approach by means of an experiment in which we highlight regions in a painting by Monet that are not very "Van Gogh-like". Taken together, we believe the tools developed in this study are well capable of assisting for art historians in support of their study of paintings.

Reducing charging effects in scanning electron microscope images by Rayleigh contrast stretching method (RCS).

PubMed

Wan Ismail, W Z; Sim, K S; Tso, C P; Ting, H Y

2011-01-01

To reduce undesirable charging effects in scanning electron microscope images, Rayleigh contrast stretching is developed and employed. First, re-scaling is performed on the input image histograms with Rayleigh algorithm. Then, contrast stretching or contrast adjustment is implemented to improve the images while reducing the contrast charging artifacts. This technique has been compared to some existing histogram equalization (HE) extension techniques: recursive sub-image HE, contrast stretching dynamic HE, multipeak HE and recursive mean separate HE. Other post processing methods, such as wavelet approach, spatial filtering, and exponential contrast stretching, are compared as well. Overall, the proposed method produces better image compensation in reducing charging artifacts. Copyright © 2011 Wiley Periodicals, Inc.

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

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.

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.

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

Esophageal wall dose-surface maps do not improve the predictive performance of a multivariable NTCP model for acute esophageal toxicity in advanced stage NSCLC patients treated with intensity-modulated (chemo-)radiotherapy.

PubMed

Dankers, Frank; Wijsman, Robin; Troost, Esther G C; Monshouwer, René; Bussink, Johan; Hoffmann, Aswin L

2017-05-07

In our previous work, a multivariable normal-tissue complication probability (NTCP) model for acute esophageal toxicity (AET) Grade  ⩾2 after highly conformal (chemo-)radiotherapy for non-small cell lung cancer (NSCLC) was developed using multivariable logistic regression analysis incorporating clinical parameters and mean esophageal dose (MED). Since the esophagus is a tubular organ, spatial information of the esophageal wall dose distribution may be important in predicting AET. We investigated whether the incorporation of esophageal wall dose-surface data with spatial information improves the predictive power of our established NTCP model. For 149 NSCLC patients treated with highly conformal radiation therapy esophageal wall dose-surface histograms (DSHs) and polar dose-surface maps (DSMs) were generated. DSMs were used to generate new DSHs and dose-length-histograms that incorporate spatial information of the dose-surface distribution. From these histograms dose parameters were derived and univariate logistic regression analysis showed that they correlated significantly with AET. Following our previous work, new multivariable NTCP models were developed using the most significant dose histogram parameters based on univariate analysis (19 in total). However, the 19 new models incorporating esophageal wall dose-surface data with spatial information did not show improved predictive performance (area under the curve, AUC range 0.79-0.84) over the established multivariable NTCP model based on conventional dose-volume data (AUC  =  0.84). For prediction of AET, based on the proposed multivariable statistical approach, spatial information of the esophageal wall dose distribution is of no added value and it is sufficient to only consider MED as a predictive dosimetric parameter.

Esophageal wall dose-surface maps do not improve the predictive performance of a multivariable NTCP model for acute esophageal toxicity in advanced stage NSCLC patients treated with intensity-modulated (chemo-)radiotherapy

NASA Astrophysics Data System (ADS)

Dankers, Frank; Wijsman, Robin; Troost, Esther G. C.; Monshouwer, René; Bussink, Johan; Hoffmann, Aswin L.

2017-05-01

In our previous work, a multivariable normal-tissue complication probability (NTCP) model for acute esophageal toxicity (AET) Grade  ⩾2 after highly conformal (chemo-)radiotherapy for non-small cell lung cancer (NSCLC) was developed using multivariable logistic regression analysis incorporating clinical parameters and mean esophageal dose (MED). Since the esophagus is a tubular organ, spatial information of the esophageal wall dose distribution may be important in predicting AET. We investigated whether the incorporation of esophageal wall dose-surface data with spatial information improves the predictive power of our established NTCP model. For 149 NSCLC patients treated with highly conformal radiation therapy esophageal wall dose-surface histograms (DSHs) and polar dose-surface maps (DSMs) were generated. DSMs were used to generate new DSHs and dose-length-histograms that incorporate spatial information of the dose-surface distribution. From these histograms dose parameters were derived and univariate logistic regression analysis showed that they correlated significantly with AET. Following our previous work, new multivariable NTCP models were developed using the most significant dose histogram parameters based on univariate analysis (19 in total). However, the 19 new models incorporating esophageal wall dose-surface data with spatial information did not show improved predictive performance (area under the curve, AUC range 0.79-0.84) over the established multivariable NTCP model based on conventional dose-volume data (AUC  =  0.84). For prediction of AET, based on the proposed multivariable statistical approach, spatial information of the esophageal wall dose distribution is of no added value and it is sufficient to only consider MED as a predictive dosimetric parameter.

Laser fluorescence fluctuation excesses in molecular immunology experiments

NASA Astrophysics Data System (ADS)

Galich, N. E.; Filatov, M. V.

2007-04-01

A novel approach to statistical analysis of flow cytometry fluorescence data have been developed and applied for population analysis of blood neutrophils stained with hydroethidine during respiratory burst reaction. The staining based on intracellular oxidation hydroethidine to ethidium bromide, which intercalate into cell DNA. Fluorescence of the resultant product serves as a measure of the neutrophil ability to generate superoxide radicals after induction respiratory burst reaction by phorbol myristate acetate (PMA). It was demonstrated that polymorphonuclear leukocytes of persons with inflammatory diseases showed a considerably changed response. Cytofluorometric histograms obtained have unique information about condition of neutrophil population what might to allow a determination of the pathology processes type connecting with such inflammation. A novel approach to histogram analysis is based on analysis of high-momentum dynamic of distribution. The features of fluctuation excesses of distribution have unique information about disease under consideration.

EMG circuit design and AR analysis of EMG signs.

PubMed

Hardalaç, Firat; Canal, Rahmi

2004-12-01

In this study, electromyogram (EMG) circuit was designed and tested on 27 people. Autoregressive (AR) analysis of EMG signals recorded on the ulnar nerve region of the right hand in resting position was performed. AR method, especially in the calculation of the spectrums of stable signs, is used for frequency analysis of signs, which give frequency response as sharp peaks and valleys. In this study, as the result of AR method analysis of EMG signals frequency-time domain, frequency spectrum curves (histogram curves) were obtained. As the images belonging to these histograms were evaluated, fibrillation potential widths of the muscle fibers of the ulnar nerve region of the people (material of the study) were examined. According to the degeneration degrees of the motor nerves, nine people had myopathy, nine had neuropathy, and nine were normal.

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.

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

Evaluation and statistical judgement of neural responses to sinusoidal stimulation in cases with superimposed drift and noise.

PubMed

Jastreboff, P W

1979-06-01

Time histograms of neural responses evoked by sinuosidal stimulation often contain a slow drifting and an irregular noise which disturb Fourier analysis of these responses. Section 2 of this paper evaluates the extent to which a linear drift influences the Fourier analysis, and develops a combined Fourier and linear regression analysis for detecting and correcting for such a linear drift. Usefulness of this correcting method is demonstrated for the time histograms of actual eye movements and Purkinje cell discharges evoked by sinusoidal rotation of rabbits in the horizontal plane. In Sect. 3, the analysis of variance is adopted for estimating the probability of the random occurrence of the response curve extracted by Fourier analysis from noise. This method proved to be useful for avoiding false judgements as to whether the response curve was meaningful, particularly when the response was small relative to the contaminating noise.

Fast Depiction Invariant Visual Similarity for Content Based Image Retrieval Based on Data-driven Visual Similarity using Linear Discriminant Analysis

NASA Astrophysics Data System (ADS)

Wihardi, Y.; Setiawan, W.; Nugraha, E.

2018-01-01

On this research we try to build CBIRS based on Learning Distance/Similarity Function using Linear Discriminant Analysis (LDA) and Histogram of Oriented Gradient (HoG) feature. Our method is invariant to depiction of image, such as similarity of image to image, sketch to image, and painting to image. LDA can decrease execution time compared to state of the art method, but it still needs an improvement in term of accuracy. Inaccuracy in our experiment happen because we did not perform sliding windows search and because of low number of negative samples as natural-world images.

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

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.

Analysis of memory use for improved design and compile-time allocation of local memory

NASA Technical Reports Server (NTRS)

Mcniven, Geoffrey D.; Davidson, Edward S.

1986-01-01

Trace analysis techniques are used to study memory referencing behavior for the purpose of designing local memories and determining how to allocate them for data and instructions. In an attempt to assess the inherent behavior of the source code, the trace analysis system described here reduced the effects of the compiler and host architecture on the trace by using a technical called flattening. The variables in the trace, their associated single-assignment values, and references are histogrammed on the basis of various parameters describing memory referencing behavior. Bounds are developed specifying the amount of memory space required to store all live values in a particular histogram class. The reduction achieved in main memory traffic by allocating local memory is specified for each class.

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

Parenchymal texture analysis in digital mammography: robust texture feature identification and equivalence across devices.

PubMed

Keller, Brad M; Oustimov, Andrew; Wang, Yan; Chen, Jinbo; Acciavatti, Raymond J; Zheng, Yuanjie; Ray, Shonket; Gee, James C; Maidment, Andrew D A; Kontos, Despina

2015-04-01

An analytical framework is presented for evaluating the equivalence of parenchymal texture features across different full-field digital mammography (FFDM) systems using a physical breast phantom. Phantom images (FOR PROCESSING) are acquired from three FFDM systems using their automated exposure control setting. A panel of texture features, including gray-level histogram, co-occurrence, run length, and structural descriptors, are extracted. To identify features that are robust across imaging systems, a series of equivalence tests are performed on the feature distributions, in which the extent of their intersystem variation is compared to their intrasystem variation via the Hodges-Lehmann test statistic. Overall, histogram and structural features tend to be most robust across all systems, and certain features, such as edge enhancement, tend to be more robust to intergenerational differences between detectors of a single vendor than to intervendor differences. Texture features extracted from larger regions of interest (i.e., [Formula: see text]) and with a larger offset length (i.e., [Formula: see text]), when applicable, also appear to be more robust across imaging systems. This framework and observations from our experiments may benefit applications utilizing mammographic texture analysis on images acquired in multivendor settings, such as in multicenter studies of computer-aided detection and breast cancer risk assessment.

Automatic lesion boundary detection in dermoscopy images using gradient vector flow snakes

PubMed Central

Erkol, Bulent; Moss, Randy H.; Stanley, R. Joe; Stoecker, William V.; Hvatum, Erik

2011-01-01

Background Malignant melanoma has a good prognosis if treated early. Dermoscopy images of pigmented lesions are most commonly taken at × 10 magnification under lighting at a low angle of incidence while the skin is immersed in oil under a glass plate. Accurate skin lesion segmentation from the background skin is important because some of the features anticipated to be used for diagnosis deal with shape of the lesion and others deal with the color of the lesion compared with the color of the surrounding skin. Methods In this research, gradient vector flow (GVF) snakes are investigated to find the border of skin lesions in dermoscopy images. An automatic initialization method is introduced to make the skin lesion border determination process fully automated. Results Skin lesion segmentation results are presented for 70 benign and 30 melanoma skin lesion images for the GVF-based method and a color histogram analysis technique. The average errors obtained by the GVF-based method are lower for both the benign and melanoma image sets than for the color histogram analysis technique based on comparison with manually segmented lesions determined by a dermatologist. Conclusions The experimental results for the GVF-based method demonstrate promise as an automated technique for skin lesion segmentation in dermoscopy images. PMID:15691255

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

PubMed

Xu, Songhua; Krauthammer, Michael

2010-12-01

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

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

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.

Free energies from dynamic weighted histogram analysis using unbiased Markov state model.

PubMed

Rosta, Edina; Hummer, Gerhard

2015-01-13

The weighted histogram analysis method (WHAM) is widely used to obtain accurate free energies from biased molecular simulations. However, WHAM free energies can exhibit significant errors if some of the biasing windows are not fully equilibrated. To account for the lack of full equilibration, we develop the dynamic histogram analysis method (DHAM). DHAM uses a global Markov state model to obtain the free energy along the reaction coordinate. A maximum likelihood estimate of the Markov transition matrix is constructed by joint unbiasing of the transition counts from multiple umbrella-sampling simulations along discretized reaction coordinates. The free energy profile is the stationary distribution of the resulting Markov matrix. For this matrix, we derive an explicit approximation that does not require the usual iterative solution of WHAM. We apply DHAM to model systems, a chemical reaction in water treated using quantum-mechanics/molecular-mechanics (QM/MM) simulations, and the Na(+) ion passage through the membrane-embedded ion channel GLIC. We find that DHAM gives accurate free energies even in cases where WHAM fails. In addition, DHAM provides kinetic information, which we here use to assess the extent of convergence in each of the simulation windows. DHAM may also prove useful in the construction of Markov state models from biased simulations in phase-space regions with otherwise low population.

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.

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.

Comparison of adverse effects of proton and X-ray chemoradiotherapy for esophageal cancer using an adaptive dose–volume histogram analysis

PubMed Central

Makishima, Hirokazu; Ishikawa, Hitoshi; Terunuma, Toshiyuki; Hashimoto, Takayuki; Yamanashi, Koichi; Sekiguchi, Takao; Mizumoto, Masashi; Okumura, Toshiyuki; Sakae, Takeji; Sakurai, Hideyuki

2015-01-01

Cardiopulmonary late toxicity is of concern in concurrent chemoradiotherapy (CCRT) for esophageal cancer. The aim of this study was to examine the benefit of proton beam therapy (PBT) using clinical data and adaptive dose–volume histogram (DVH) analysis. The subjects were 44 patients with esophageal cancer who underwent definitive CCRT using X-rays (n = 19) or protons (n = 25). Experimental recalculation using protons was performed for the patient actually treated with X-rays, and vice versa. Target coverage and dose constraints of normal tissues were conserved. Lung V5–V20, mean lung dose (MLD), and heart V30–V50 were compared for risk organ doses between experimental plans and actual treatment plans. Potential toxicity was estimated using protons in patients actually treated with X-rays, and vice versa. Pulmonary events of Grade ≥2 occurred in 8/44 cases (18%), and cardiac events were seen in 11 cases (25%). Risk organ doses in patients with events of Grade ≥2 were significantly higher than for those with events of Grade ≤1. Risk organ doses were lower in proton plans compared with X-ray plans. All patients suffering toxicity who were treated with X-rays (n = 13) had reduced predicted doses in lung and heart using protons, while doses in all patients treated with protons (n = 24) with toxicity of Grade ≤1 had worsened predicted toxicity with X-rays. Analysis of normal tissue complication probability showed a potential reduction in toxicity by using proton beams. Irradiation dose, volume and adverse effects on the heart and lung can be reduced using protons. Thus, PBT is a promising treatment modality for the management of esophageal cancer. PMID:25755255

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

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

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.

Human Papillomavirus and Epidermal Growth Factor Receptor in Oral Cavity and Oropharyngeal Squamous Cell Carcinoma: Correlation With Dynamic Contrast-Enhanced MRI Parameters.

PubMed

Choi, Yoon Seong; Park, Mina; Kwon, Hyeong Ju; Koh, Yoon Woo; Lee, Seung-Koo; Kim, Jinna

2016-02-01

The objective of this study was to investigate differences in dynamic contrast-enhanced MRI (DCE-MRI) parameters on the basis of the status of human papillomavirus (HPV) and epidermal growth factor receptor (EGFR) biomarkers in patients with squamous cell carcinoma (SCC) of the oral cavity and oropharynx by use of histogram analysis. A total of 22 consecutive patients with oral cavity and oropharyngeal SCC underwent DCE-MRI before receiving treatment. DCE parameter maps of the volume transfer constant (K(trans)), the flux rate constant (kep), and the extravascular extracellular volume fraction (ve) were obtained. The histogram parameters were calculated using the entire enhancing tumor volume and were compared between the patient subgroups on the basis of HPV and EGFR biomarker statuses. The cumulative histogram parameters of K(trans) and kep showed lower values in the HPV-negative and EFGR-overexpression group than in the HPV-positive EGFR-negative group. These differences were statistically significant for the mean (p = 0.009), 25th, 50th, and 75th percentile values of K(trans) and for the 25th percentile value of kep when correlated with HPV status in addition to the mean K(trans) value (p = 0.047) and kep value (p = 0.004) when correlated with EGFR status. No statistically significant difference in ve was found on the basis of HPV and EGFR status. DCE-MRI is useful for the assessment of the tumor microenvironment associated with HPV and EGFR biomarkers before treatment of patients with oral cavity and oropharyngeal SCC.

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.

Detection of simulated microcalcifications in fixed mammary tissue: An ROC study of the effect of local versus global histogram equalization.

PubMed

Sund, T; Olsen, J B

2006-09-01

To investigate whether sliding window adaptive histogram equalization (SWAHE) of digital mammograms improves the detection of simulated calcifications, as compared to images normalized by global histogram equalization (GHE). Direct digital mammograms were obtained from mammary tissue phantoms superimposed with different frames. Each frame was divided into forty squares by a wire mesh, and contained granular calcifications randomly positioned in about 50% of the squares. Three radiologists read the mammograms on a display monitor. They classified their confidence in the presence of microcalcifications in each square on a scale of 1 to 5. Images processed with GHE were first read and used as a reference. In a later session, the same images processed with SWAHE were read. The results were compared using ROC methodology. When the total areas AZ were compared, the results were completely equivocal. When comparing the high-specificity partial ROC area AZ,0.2 below false-positive fraction (FPF) 0.20, two of the three observers performed best with the images processed with SWAHE. The difference was not statistically significant. When the reader's confidence threshold in malignancy is set at a high level, increasing the contrast of mammograms with SWAHE may enhance the visibility of microcalcifications without adversely affecting the false-positive rate. When the reader's confidence threshold is set at a low level, the effect of SWAHE is an increase of false positives. Further investigation is needed to confirm the validity of the conclusions.

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.

[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.

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.

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.

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.

LEDs as light source: examining quality of acquired images

NASA Astrophysics Data System (ADS)

Bachnak, Rafic; Funtanilla, Jeng; Hernandez, Jose

2004-05-01

Recent advances in technology have made light emitting diodes (LEDs) viable in a number of applications, including vehicle stoplights, traffic lights, machine-vision-inspection, illumination, and street signs. This paper presents the results of comparing images taken by a videoscope using two different light sources. One of the sources is the internal metal halide lamp and the other is a LED placed at the tip of the insertion tube. Images acquired using these two light sources were quantitatively compared using their histogram, intensity profile along a line segment, and edge detection. Also, images were qualitatively compared using image registration and transformation. The gray-level histogram, edge detection, image profile and image registration do not offer conclusive results. The LED light source, however, produces good images for visual inspection by an operator. The paper will present the results and discuss the usefulness and shortcomings of various comparison methods.

Application of whole-lesion histogram analysis of pharmacokinetic parameters in dynamic contrast-enhanced MRI of breast lesions with the CAIPIRINHA-Dixon-TWIST-VIBE technique.

PubMed

Li, Zhiwei; Ai, Tao; Hu, Yiqi; Yan, Xu; Nickel, Marcel Dominik; Xu, Xiao; Xia, Liming

2018-01-01

To investigate the application of whole-lesion histogram analysis of pharmacokinetic parameters for differentiating malignant from benign breast lesions on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In all, 92 women with 97 breast lesions (26 benign and 71 malignant lesions) were enrolled in this study. Patients underwent dynamic breast MRI at 3T using a prototypical CAIPIRINHA-Dixon-TWIST-VIBE (CDT-VIBE) sequence and a subsequent surgery or biopsy. Inflow rate of the agent between plasma and interstitium (K trans ), outflow rate of agent between interstitium and plasma (K ep ), extravascular space volume per unit volume of tissue (v e ) including mean value, 25th/50th/75th/90th percentiles, skewness, and kurtosis were then calculated based on the whole lesion. A single-sample Kolmogorov-Smirnov test, paired t-test, and receiver operating characteristic curve (ROC) analysis were used for statistical analysis. Malignant breast lesions had significantly higher K trans , K ep , and lower v e in mean values, 25th/50th/75th/90th percentiles, and significantly higher skewness of v e than benign breast lesions (all P < 0.05). There was no significant difference in kurtosis values between malignant and benign breast lesions (all P > 0.05). The 90th percentile of K trans , the 90th percentile of K ep , and the 50th percentile of v e showed the greatest areas under the ROC curve (AUC) for each pharmacokinetic parameter derived from DCE-MRI. The 90th percentile of K ep achieved the highest AUC value (0.927) among all histogram-derived values. The whole-lesion histogram analysis of pharmacokinetic parameters can improve the diagnostic accuracy of breast DCE-MRI with the CDT-VIBE technique. The 90th percentile of K ep may be the best indicator in differentiation between malignant and benign breast lesions. 4 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2018;47:91-96. © 2017 International Society for Magnetic Resonance in Medicine.

A comparison of two methods for expert elicitation in health technology assessments.

PubMed

Grigore, Bogdan; Peters, Jaime; Hyde, Christopher; Stein, Ken

2016-07-26

When data needed to inform parameters in decision models are lacking, formal elicitation of expert judgement can be used to characterise parameter uncertainty. Although numerous methods for eliciting expert opinion as probability distributions exist, there is little research to suggest whether one method is more useful than any other method. This study had three objectives: (i) to obtain subjective probability distributions characterising parameter uncertainty in the context of a health technology assessment; (ii) to compare two elicitation methods by eliciting the same parameters in different ways; (iii) to collect subjective preferences of the experts for the different elicitation methods used. Twenty-seven clinical experts were invited to participate in an elicitation exercise to inform a published model-based cost-effectiveness analysis of alternative treatments for prostate cancer. Participants were individually asked to express their judgements as probability distributions using two different methods - the histogram and hybrid elicitation methods - presented in a random order. Individual distributions were mathematically aggregated across experts with and without weighting. The resulting combined distributions were used in the probabilistic analysis of the decision model and mean incremental cost-effectiveness ratios and the expected values of perfect information (EVPI) were calculated for each method, and compared with the original cost-effectiveness analysis. Scores on the ease of use of the two methods and the extent to which the probability distributions obtained from each method accurately reflected the expert's opinion were also recorded. Six experts completed the task. Mean ICERs from the probabilistic analysis ranged between £162,600-£175,500 per quality-adjusted life year (QALY) depending on the elicitation and weighting methods used. Compared to having no information, use of expert opinion decreased decision uncertainty: the EVPI value at the £30,000 per QALY threshold decreased by 74-86 % from the original cost-effectiveness analysis. Experts indicated that the histogram method was easier to use, but attributed a perception of more accuracy to the hybrid method. Inclusion of expert elicitation can decrease decision uncertainty. Here, choice of method did not affect the overall cost-effectiveness conclusions, but researchers intending to use expert elicitation need to be aware of the impact different methods could have.

A comparative statistical study of long-term agroclimatic conditions affecting the growth of US winter wheat: Distributions of regional monthly average precipitation on the Great Plains and the state of Maryland and the effect of agroclimatic conditions on yield in the state of Kansas

NASA Technical Reports Server (NTRS)

Welker, J.

1981-01-01

A histogram analysis of average monthly precipitation over 30 and 84 year periods for both Maryland and Kansas was made and the results compared. A second analysis, a statistical assessment of the effect of average monthly precipitation on Kansas winter wheat yield was made. The data sets covered the three periods of 1941-1970, 1887-1970, and 1887-1921. Analyses of the limited data sets used (only the average monthly precipitation and temperature were correlated against yield) indicated that fall precipitation values, especially those of September and October, were more important to winter wheat yield than were spring values, particularly for the period 1941-1970.

Multivariable nonlinear analysis of foreign exchange rates

NASA Astrophysics Data System (ADS)

Suzuki, Tomoya; Ikeguchi, Tohru; Suzuki, Masuo

2003-05-01

We analyze the multivariable time series of foreign exchange rates. These are price movements that have often been analyzed, and dealing time intervals and spreads between bid and ask prices. Considering dealing time intervals as event timing such as neurons’ firings, we use raster plots (RPs) and peri-stimulus time histograms (PSTHs) which are popular methods in the field of neurophysiology. Introducing special processings to obtaining RPs and PSTHs time histograms for analyzing exchange rates time series, we discover that there exists dynamical interaction among three variables. We also find that adopting multivariables leads to improvements of prediction accuracy.

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.

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.

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.

Analysis of Doppler radar windshear data

NASA Technical Reports Server (NTRS)

Williams, F.; Mckinney, P.; Ozmen, F.

1989-01-01

The objective of this analysis is to process Lincoln Laboratory Doppler radar data obtained during FLOWS testing at Huntsville, Alabama, in the summer of 1986, to characterize windshear events. The processing includes plotting velocity and F-factor profiles, histogram analysis to summarize statistics, and correlation analysis to demonstrate any correlation between different data fields.

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.

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.

Skin temperature evaluation by infrared thermography: Comparison of two image analysis methods during the nonsteady state induced by physical exercise

NASA Astrophysics Data System (ADS)

Formenti, Damiano; Ludwig, Nicola; Rossi, Alessio; Trecroci, Athos; Alberti, Giampietro; Gargano, Marco; Merla, Arcangelo; Ammer, Kurt; Caumo, Andrea

2017-03-01

The most common method to derive a temperature value from a thermal image in humans is the calculation of the average of the temperature values of all the pixels confined within a demarcated boundary defined region of interest (ROI). Such summary measure of skin temperature is denoted as Troi in this study. Recently, an alternative method for the derivation of skin temperature from the thermal image has been developed. Such novel method (denoted as Tmax) is based on an automated (software-driven) selection of the warmest pixels within the ROI. Troi and Tmax have been compared under basal, steady-state conditions, resulting very well correlated and characterized by a bias of approximately 1 °C (Tmax > Troi). Aim of this study was to investigate the relationship between Tmax and Troi under the nonsteady-state conditions induced by physical exercise. Thermal images of quadriceps of 13 subjects performing a squat exercise were recorded for 120 s before (basal steady state) and for 480 s after the initiation of the exercise (nonsteady state). The thermal images were then analysed to extract Troi and Tmax. Troi and Tmax changed almost in parallel during the nonstead -state. At a closer inspection, it was found that during the nonsteady state the bias between the two methods slightly increased (from 0.7 to 1.1 °C) and the degree of association between them slightly decreased (from Pearson's r = 0.96 to 0.83). Troi and Tmax had different relationships with the skin temperature histogram. Whereas Tmax was the mean, which could be interpreted as the centre of gravity of the histogram, Tmax was related with the extreme upper tail of the histogram. During the nonsteady state, the histogram increased its spread and became slightly more asymmetric. As a result, Troi deviated a little from the 50th percentile, while Tmax remained constantly higher than the 95th percentile. Despite their differences, Troi and Tmax showed a substantial agreement in assessing the changes in skin temperature following physical exercise. Further studies are needed to clarify the relationship existing among Tmax, Troi and cutaneous blood flow during physical exercise.

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.

The Amazing Histogram.

ERIC Educational Resources Information Center

Vandermeulen, H.; DeWreede, R. E.

1983-01-01

Presents a histogram drawing program which sorts real numbers in up to 30 categories. Entered data are sorted and saved in a text file which is then used to generate the histogram. Complete Applesoft program listings are included. (JN)

An analysis of automatic human detection and tracking

NASA Astrophysics Data System (ADS)

Demuth, Philipe R.; Cosmo, Daniel L.; Ciarelli, Patrick M.

2015-12-01

This paper presents an automatic method to detect and follow people on video streams. This method uses two techniques to determine the initial position of the person at the beginning of the video file: one based on optical flow and the other one based on Histogram of Oriented Gradients (HOG). After defining the initial bounding box, tracking is done using four different trackers: Median Flow tracker, TLD tracker, Mean Shift tracker and a modified version of the Mean Shift tracker using HSV color space. The results of the methods presented in this paper are then compared at the end of the paper.

End-to-end workflow for finite element analysis of tumor treating fields in glioblastomas

NASA Astrophysics Data System (ADS)

Timmons, Joshua J.; Lok, Edwin; San, Pyay; Bui, Kevin; Wong, Eric T.

2017-11-01

Tumor Treating Fields (TTFields) therapy is an approved modality of treatment for glioblastoma. Patient anatomy-based finite element analysis (FEA) has the potential to reveal not only how these fields affect tumor control but also how to improve efficacy. While the automated tools for segmentation speed up the generation of FEA models, multi-step manual corrections are required, including removal of disconnected voxels, incorporation of unsegmented structures and the addition of 36 electrodes plus gel layers matching the TTFields transducers. Existing approaches are also not scalable for the high throughput analysis of large patient volumes. A semi-automated workflow was developed to prepare FEA models for TTFields mapping in the human brain. Magnetic resonance imaging (MRI) pre-processing, segmentation, electrode and gel placement, and post-processing were all automated. The material properties of each tissue were applied to their corresponding mask in silico using COMSOL Multiphysics (COMSOL, Burlington, MA, USA). The fidelity of the segmentations with and without post-processing was compared against the full semi-automated segmentation workflow approach using Dice coefficient analysis. The average relative differences for the electric fields generated by COMSOL were calculated in addition to observed differences in electric field-volume histograms. Furthermore, the mesh file formats in MPHTXT and NASTRAN were also compared using the differences in the electric field-volume histogram. The Dice coefficient was less for auto-segmentation without versus auto-segmentation with post-processing, indicating convergence on a manually corrected model. An existent but marginal relative difference of electric field maps from models with manual correction versus those without was identified, and a clear advantage of using the NASTRAN mesh file format was found. The software and workflow outlined in this article may be used to accelerate the investigation of TTFields in glioblastoma patients by facilitating the creation of FEA models derived from patient MRI datasets.

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.

Detection and tracking of gas plumes in LWIR hyperspectral video sequence data

NASA Astrophysics Data System (ADS)

Gerhart, Torin; Sunu, Justin; Lieu, Lauren; Merkurjev, Ekaterina; Chang, Jen-Mei; Gilles, Jérôme; Bertozzi, Andrea L.

2013-05-01

Automated detection of chemical plumes presents a segmentation challenge. The segmentation problem for gas plumes is difficult due to the diffusive nature of the cloud. The advantage of considering hyperspectral images in the gas plume detection problem over the conventional RGB imagery is the presence of non-visual data, allowing for a richer representation of information. In this paper we present an effective method of visualizing hyperspectral video sequences containing chemical plumes and investigate the effectiveness of segmentation techniques on these post-processed videos. Our approach uses a combination of dimension reduction and histogram equalization to prepare the hyperspectral videos for segmentation. First, Principal Components Analysis (PCA) is used to reduce the dimension of the entire video sequence. This is done by projecting each pixel onto the first few Principal Components resulting in a type of spectral filter. Next, a Midway method for histogram equalization is used. These methods redistribute the intensity values in order to reduce icker between frames. This properly prepares these high-dimensional video sequences for more traditional segmentation techniques. We compare the ability of various clustering techniques to properly segment the chemical plume. These include K-means, spectral clustering, and the Ginzburg-Landau functional.

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 %.

MO-FG-202-06: Improving the Performance of Gamma Analysis QA with Radiomics- Based Image Analysis

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

Wootton, L; Nyflot, M; Ford, E

2016-06-15

Purpose: The use of gamma analysis for IMRT quality assurance has well-known limitations. Traditionally, a simple thresholding technique is used to evaluated passing criteria. However, like any image the gamma distribution is rich in information which thresholding mostly discards. We therefore propose a novel method of analyzing gamma images that uses quantitative image features borrowed from radiomics, with the goal of improving error detection. Methods: 368 gamma images were generated from 184 clinical IMRT beams. For each beam the dose to a phantom was measured with EPID dosimetry and compared to the TPS dose calculated with and without normally distributedmore » (2mm sigma) errors in MLC positions. The magnitude of 17 intensity histogram and size-zone radiomic features were derived from each image. The features that differed most significantly between image sets were determined with ROC analysis. A linear machine-learning model was trained on these features to classify images as with or without errors on 180 gamma images.The model was then applied to an independent validation set of 188 additional gamma distributions, half with and half without errors. Results: The most significant features for detecting errors were histogram kurtosis (p=0.007) and three size-zone metrics (p<1e-6 for each). The sizezone metrics detected clusters of high gamma-value pixels under mispositioned MLCs. The model applied to the validation set had an AUC of 0.8, compared to 0.56 for traditional gamma analysis with the decision threshold restricted to 98% or less. Conclusion: A radiomics-based image analysis method was developed that is more effective in detecting error than traditional gamma analysis. Though the pilot study here considers only MLC position errors, radiomics-based methods for other error types are being developed, which may provide better error detection and useful information on the source of detected errors. This work was partially supported by a grant from the Agency for Healthcare Research and Quality, grant number R18 HS022244-01.« less

ARM Radar Contoured Frequency by Altitude Diagram (CFAD) Data Products

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

Zhang, Yuying

2017-03-10

To compare with ARM cloud radar simulator outputs, observational reflectivity-height joint histograms, i.e., CFADs, are constructed from the operational ARM Active Remote Sensing of CLouds (ARSCL) Value-Added Product.

An embedded face-classification system for infrared images on an FPGA

NASA Astrophysics Data System (ADS)

Soto, Javier E.; Figueroa, Miguel

2014-10-01

We present a face-classification architecture for long-wave infrared (IR) images implemented on a Field Programmable Gate Array (FPGA). The circuit is fast, compact and low power, can recognize faces in real time and be embedded in a larger image-processing and computer vision system operating locally on an IR camera. The algorithm uses Local Binary Patterns (LBP) to perform feature extraction on each IR image. First, each pixel in the image is represented as an LBP pattern that encodes the similarity between the pixel and its neighbors. Uniform LBP codes are then used to reduce the number of patterns to 59 while preserving more than 90% of the information contained in the original LBP representation. Then, the image is divided into 64 non-overlapping regions, and each region is represented as a 59-bin histogram of patterns. Finally, the algorithm concatenates all 64 regions to create a 3,776-bin spatially enhanced histogram. We reduce the dimensionality of this histogram using Linear Discriminant Analysis (LDA), which improves clustering and enables us to store an entire database of 53 subjects on-chip. During classification, the circuit applies LBP and LDA to each incoming IR image in real time, and compares the resulting feature vector to each pattern stored in the local database using the Manhattan distance. We implemented the circuit on a Xilinx Artix-7 XC7A100T FPGA and tested it with the UCHThermalFace database, which consists of 28 81 x 150-pixel images of 53 subjects in indoor and outdoor conditions. The circuit achieves a 98.6% hit ratio, trained with 16 images and tested with 12 images of each subject in the database. Using a 100 MHz clock, the circuit classifies 8,230 images per second, and consumes only 309mW.

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

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors.

PubMed

Rodriguez Gutierrez, D; Awwad, A; Meijer, L; Manita, M; Jaspan, T; Dineen, R A; Grundy, R G; Auer, D P

2014-05-01

Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features. This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data. ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix. Support vector machine-based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology. © 2014 by American Journal of Neuroradiology.

Improving the imaging of calcifications in CT by histogram-based selective deblurring

NASA Astrophysics Data System (ADS)

Rollano-Hijarrubia, Empar; van der Meer, Frits; van der Lugt, Add; Weinans, Harrie; Vrooman, Henry; Vossepoel, Albert; Stokking, Rik

2005-04-01

Imaging of small high-density structures, such as calcifications, with computed tomography (CT) is limited by the spatial resolution of the system. Blur causes small calcifications to be imaged with lower contrast and overestimated volume, thereby hampering the analysis of vessels. The aim of this work is to reduce the blur of calcifications by applying three-dimensional (3D) deconvolution. Unfortunately, the high-frequency amplification of the deconvolution produces edge-related ring artifacts and enhances noise and original artifacts, which degrades the imaging of low-density structures. A method, referred to as Histogram-based Selective Deblurring (HiSD), was implemented to avoid these negative effects. HiSD uses the histogram information to generate a restored image in which the low-intensity voxel information of the observed image is combined with the high-intensity voxel information of the deconvolved image. To evaluate HiSD we scanned four in-vitro atherosclerotic plaques of carotid arteries with a multislice spiral CT and with a microfocus CT (μCT), used as reference. Restored images were generated from the observed images, and qualitatively and quantitatively compared with their corresponding μCT images. Transverse views and maximum-intensity projections of restored images show the decrease of blur of the calcifications in 3D. Measurements of the areas of 27 calcifications and total volumes of calcification of 4 plaques show that the overestimation of calcification was smaller for restored images (mean-error: 90% for area; 92% for volume) than for observed images (143%; 213%, respectively). The qualitative and quantitative analyses show that the imaging of calcifications in CT can be improved considerably by applying HiSD.

Free Energy Reconstruction from Metadynamics or Adiabatic Free Energy Dynamics Simulations.

PubMed

Cuendet, Michel A; Tuckerman, Mark E

2014-08-12

In molecular dynamics simulations, most enhanced sampling methods are traditionally associated with one particular estimator to calculate the free energy surface (FES), such as the histogram, the mean force, or the bias potential. Here, we start from the realization that four enhanced sampling methods, metadynamics and well-tempered metadynamics (in their extended Lagrangian form), as well as driven adiabatic free energy dynamics (dAFED) and unified free energy dynamics (UFED), can be used in combination with any of the three above-mentioned FES estimators. We compare the convergence properties of these estimators on the alanine dipeptide and a sodium ion solvation shell. We find that the mean force estimator is superior in all cases. We also show that it can be marginally beneficial to combine information from the histogram and the force, provided that both are of comparable accuracy.

Fast and straightforward analysis approach of charge transport data in single molecule junctions.

PubMed

Zhang, Qian; Liu, Chenguang; Tao, Shuhui; Yi, Ruowei; Su, Weitao; Zhao, Cezhou; Zhao, Chun; Dappe, Yannick J; Nichols, Richard J; Yang, Li

2018-08-10

In this study, we introduce an efficient data sorting algorithm, including filters for noisy signals, conductance mapping for analyzing the most dominant conductance group and sub-population groups. The capacity of our data analysis process has also been corroborated on real experimental data sets of Au-1,6-hexanedithiol-Au and Au-1,8-octanedithiol-Au molecular junctions. The fully automated and unsupervised program requires less than one minute on a standard PC to sort the data and generate histograms. The resulting one-dimensional and two-dimensional log histograms give conductance values in good agreement with previous studies. Our algorithm is a straightforward, fast and user-friendly tool for single molecule charge transport data analysis. We also analyze the data in a form of a conductance map which can offer evidence for diversity in molecular conductance. The code for automatic data analysis is openly available, well-documented and ready to use, thereby offering a useful new tool for single molecule electronics.

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.

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.

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.

[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.

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.

Accelerating the weighted histogram analysis method by direct inversion in the iterative subspace.

PubMed

Zhang, Cheng; Lai, Chun-Liang; Pettitt, B Montgomery

The weighted histogram analysis method (WHAM) for free energy calculations is a valuable tool to produce free energy differences with the minimal errors. Given multiple simulations, WHAM obtains from the distribution overlaps the optimal statistical estimator of the density of states, from which the free energy differences can be computed. The WHAM equations are often solved by an iterative procedure. In this work, we use a well-known linear algebra algorithm which allows for more rapid convergence to the solution. We find that the computational complexity of the iterative solution to WHAM and the closely-related multiple Bennett acceptance ratio (MBAR) method can be improved by using the method of direct inversion in the iterative subspace. We give examples from a lattice model, a simple liquid and an aqueous protein solution.

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.

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.

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.…

An application to pulmonary emphysema classification based on model of texton learning by sparse representation

NASA Astrophysics Data System (ADS)

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

2012-03-01

We aim at using a new texton based texture classification method in the classification of pulmonary emphysema in computed tomography (CT) images of the lungs. Different from conventional computer-aided diagnosis (CAD) pulmonary emphysema classification methods, in this paper, firstly, the dictionary of texton is learned via applying sparse representation(SR) to image patches in the training dataset. Then the SR coefficients of the test images over the dictionary are used to construct the histograms for texture presentations. Finally, classification is performed by using a nearest neighbor classifier with a histogram dissimilarity measure as distance. The proposed approach is tested on 3840 annotated regions of interest consisting of normal tissue and mild, moderate and severe pulmonary emphysema of three subtypes. The performance of the proposed system, with an accuracy of about 88%, is comparably higher than state of the art method based on the basic rotation invariant local binary pattern histograms and the texture classification method based on texton learning by k-means, which performs almost the best among other approaches in the literature.

Regime-Dependent Differences in Surface Freshwater Exchange Estimates Over the Ocean

NASA Astrophysics Data System (ADS)

Wong, Sun; Behrangi, Ali

2018-01-01

Differences in gridded precipitation (P), surface evaporation (E), and the resultant surface freshwater exchange (P - E) among different products over the ocean are diagnosed as functions of moisture advection (Qadvt) and moisture tendency by dynamical convergence (Qcnvg). Compared to the GPCP product, the TRMM3B42 product captures higher frequency of precipitation with larger extreme precipitation rates in regimes of deep convection and more light rain detections in regimes of frequent occurrence of boundary layer clouds. Discrepancies in E depend on moisture flux divergence, with the OAFlux product having the largest E in regimes of divergence. Discrepancies in mean P - E in deep convective regimes are highly influenced by differences in precipitation, with the TRMM3B42 product yielding P - E histograms closer to those inferred from the reanalysis moisture flux convergence. In nonconvergent regimes, observation-based P - E histograms skew toward positive values while the inferred reanalysis histograms are symmetric about the means.

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…

Differentiation of Recurrent Glioblastoma from Delayed Radiation Necrosis by Using Voxel-based Multiparametric Analysis of MR Imaging Data.

PubMed

Yoon, Ra Gyoung; Kim, Ho Sung; Koh, Myeong Ju; Shim, Woo Hyun; Jung, Seung Chai; Kim, Sang Joon; Kim, Jeong Hoon

2017-10-01

Purpose To assess a volume-weighted voxel-based multiparametric (MP) clustering method as an imaging biomarker to differentiate recurrent glioblastoma from delayed radiation necrosis. Materials and Methods The institutional review board approved this retrospective study and waived the informed consent requirement. Seventy-five patients with pathologic analysis-confirmed recurrent glioblastoma (n = 42) or radiation necrosis (n = 33) who presented with enlarged contrast material-enhanced lesions at magnetic resonance (MR) imaging after they completed concurrent chemotherapy and radiation therapy were enrolled. The diagnostic performance of the total MP cluster score was determined by using the area under the receiver operating characteristic curve (AUC) with cross-validation and compared with those of single parameter measurements (10% histogram cutoffs of apparent diffusion coefficient [ADC10] or 90% histogram cutoffs of normalized cerebral blood volume and initial time-signal intensity AUC). Results Receiver operating characteristic curve analysis showed that an AUC for differentiating recurrent glioblastoma from delayed radiation necrosis was highest in the total MP cluster score and lowest for ADC10 for both readers. The total MP cluster score had significantly better diagnostic accuracy than any single parameter (corrected P = .001-.039 for reader 1; corrected P = .005-.041 for reader 2). The total MP cluster score was the best predictor of recurrent glioblastoma (cross-validated AUCs, 0.942-0.946 for both readers), with a sensitivity of 95.2% for reader 1 and 97.6% for reader 2. Conclusion Quantitative analysis with volume-weighted voxel-based MP clustering appears to be superior to the use of single imaging parameters to differentiate recurrent glioblastoma from delayed radiation necrosis. © RSNA, 2017 Online supplemental material is available for this article.

An evaluation of the effectiveness of adaptive histogram equalization for contrast enhancement.

PubMed

Zimmerman, J B; Pizer, S M; Staab, E V; Perry, J R; McCartney, W; Brenton, B C

1988-01-01

Adaptive histogram equalization (AHE) and intensity windowing have been compared using psychophysical observer studies. Experienced radiologists were shown clinical CT (computerized tomographic) images of the chest. Into some of the images, appropriate artificial lesions were introduced; the physicians were then shown the images processed with both AHE and intensity windowing. They were asked to assess the probability that a given image contained the artificial lesion, and their accuracy was measured. The results of these experiments show that for this particular diagnostic task, there was no significant difference in the ability of the two methods to depict luminance contrast; thus, further evaluation of AHE using controlled clinical trials is indicated.

Effective structural descriptors for natural and engineered radioactive waste confinement barriers

NASA Astrophysics Data System (ADS)

Lemmens, Laurent; Rogiers, Bart; De Craen, Mieke; Laloy, Eric; Jacques, Diederik; Huysmans, Marijke; Swennen, Rudy; Urai, Janos L.; Desbois, Guillaume

2017-04-01

The microstructure of a radioactive waste confinement barrier strongly influences its flow and transport properties. Numerical flow and transport simulations for these porous media at the pore scale therefore require input data that describe the microstructure as accurately as possible. To date, no imaging method can resolve all heterogeneities within important radioactive waste confinement barrier materials as hardened cement paste and natural clays at the micro scale (nm-cm). Therefore, it is necessary to merge information from different 2D and 3D imaging methods using porous media reconstruction techniques. To qualitatively compare the results of different reconstruction techniques, visual inspection might suffice. To quantitatively compare training-image based algorithms, Tan et al. (2014) proposed an algorithm using an analysis of distance. However, the ranking of the algorithm depends on the choice of the structural descriptor, in their case multiple-point or cluster-based histograms. We present here preliminary work in which we will review different structural descriptors and test their effectiveness, for capturing the main structural characteristics of radioactive waste confinement barrier materials, to determine the descriptors to use in the analysis of distance. The investigated descriptors are particle size distributions, surface area distributions, two point probability functions, multiple point histograms, linear functions and two point cluster functions. The descriptor testing consists of stochastically generating realizations from a reference image using the simulated annealing optimization procedure introduced by Karsanina et al. (2015). This procedure basically minimizes the differences between pre-specified descriptor values associated with the training image and the image being produced. The most efficient descriptor set can therefore be identified by comparing the image generation quality among the tested descriptor combinations. The assessment of the quality of the simulations will be made by combining all considered descriptors. Once the set of the most efficient descriptors is determined, they can be used in the analysis of distance, to rank different reconstruction algorithms in a more objective way in future work. Karsanina MV, Gerke KM, Skvortsova EB, Mallants D (2015) Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure. PLoS ONE 10(5): e0126515. doi:10.1371/journal.pone.0126515 Tan, Xiaojin, Pejman Tahmasebi, and Jef Caers. "Comparing training-image based algorithms using an analysis of distance." Mathematical Geosciences 46.2 (2014): 149-169.

Classification of facial-emotion expression in the application of psychotherapy using Viola-Jones and Edge-Histogram of Oriented Gradient.

PubMed

Candra, Henry; Yuwono, Mitchell; Rifai Chai; Nguyen, Hung T; Su, Steven

2016-08-01

Psychotherapy requires appropriate recognition of patient's facial-emotion expression to provide proper treatment in psychotherapy session. To address the needs this paper proposed a facial emotion recognition system using Combination of Viola-Jones detector together with a feature descriptor we term Edge-Histogram of Oriented Gradients (E-HOG). The performance of the proposed method is compared with various feature sources including the face, the eyes, the mouth, as well as both the eyes and the mouth. Seven classes of basic emotions have been successfully identified with 96.4% accuracy using Multi-class Support Vector Machine (SVM). The proposed descriptor E-HOG is much leaner to compute compared to traditional HOG as shown by a significant improvement in processing time as high as 1833.33% (p-value = 2.43E-17) with a slight reduction in accuracy of only 1.17% (p-value = 0.0016).

Railroad Classification Yard Technology Manual. Volume III. Freight Car Rollability

DOT National Transportation Integrated Search

1981-07-01

The report presents a survey of rolling resistance research, histograms of rolling resistance from five yards, a statistical regression analysis of causal factors affecting rolling resistance, procedures for constructing a rolling resistance histogra...

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.

Quantifying the impact of immediate reconstruction in postmastectomy radiation: a large, dose-volume histogram-based analysis.

PubMed

Ohri, Nisha; Cordeiro, Peter G; Keam, Jennifer; Ballangrud, Ase; Shi, Weiji; Zhang, Zhigang; Nerbun, Claire T; Woch, Katherine M; Stein, Nicholas F; Zhou, Ying; McCormick, Beryl; Powell, Simon N; Ho, Alice Y

2012-10-01

To assess the impact of immediate breast reconstruction on postmastectomy radiation (PMRT) using dose-volume histogram (DVH) data. Two hundred forty-seven women underwent PMRT at our center, 196 with implant reconstruction and 51 without reconstruction. Patients with reconstruction were treated with tangential photons, and patients without reconstruction were treated with en-face electron fields and customized bolus. Twenty percent of patients received internal mammary node (IMN) treatment. The DVH data were compared between groups. Ipsilateral lung parameters included V20 (% volume receiving 20 Gy), V40 (% volume receiving 40 Gy), mean dose, and maximum dose. Heart parameters included V25 (% volume receiving 25 Gy), mean dose, and maximum dose. IMN coverage was assessed when applicable. Chest wall coverage was assessed in patients with reconstruction. Propensity-matched analysis adjusted for potential confounders of laterality and IMN treatment. Reconstruction was associated with lower lung V20, mean dose, and maximum dose compared with no reconstruction (all P<.0001). These associations persisted on propensity-matched analysis (all P<.0001). Heart doses were similar between groups (P=NS). Ninety percent of patients with reconstruction had excellent chest wall coverage (D95 >98%). IMN coverage was superior in patients with reconstruction (D95 >92.0 vs 75.7%, P<.001). IMN treatment significantly increased lung and heart parameters in patients with reconstruction (all P<.05) but minimally affected those without reconstruction (all P>.05). Among IMN-treated patients, only lower lung V20 in those without reconstruction persisted (P=.022), and mean and maximum heart doses were higher than in patients without reconstruction (P=.006, P=.015, respectively). Implant reconstruction does not compromise the technical quality of PMRT when the IMNs are untreated. Treatment technique, not reconstruction, is the primary determinant of target coverage and normal tissue doses. Published by Elsevier Inc.

Mutual information estimation for irregularly sampled time series

NASA Astrophysics Data System (ADS)

Rehfeld, K.; Marwan, N.; Heitzig, J.; Kurths, J.

2012-04-01

For the automated, objective and joint analysis of time series, similarity measures are crucial. Used in the analysis of climate records, they allow for a complimentary, unbiased view onto sparse datasets. The irregular sampling of many of these time series, however, makes it necessary to either perform signal reconstruction (e.g. interpolation) or to develop and use adapted measures. Standard linear interpolation comes with an inevitable loss of information and bias effects. We have recently developed a Gaussian kernel-based correlation algorithm with which the interpolation error can be substantially lowered, but this would not work should the functional relationship in a bivariate setting be non-linear. We therefore propose an algorithm to estimate lagged auto and cross mutual information from irregularly sampled time series. We have extended the standard and adaptive binning histogram estimators and use Gaussian distributed weights in the estimation of the (joint) probabilities. To test our method we have simulated linear and nonlinear auto-regressive processes with Gamma-distributed inter-sampling intervals. We have then performed a sensitivity analysis for the estimation of actual coupling length, the lag of coupling and the decorrelation time in the synthetic time series and contrast our results to the performance of a signal reconstruction scheme. Finally we applied our estimator to speleothem records. We compare the estimated memory (or decorrelation time) to that from a least-squares estimator based on fitting an auto-regressive process of order 1. The calculated (cross) mutual information results are compared for the different estimators (standard or adaptive binning) and contrasted with results from signal reconstruction. We find that the kernel-based estimator has a significantly lower root mean square error and less systematic sampling bias than the interpolation-based method. It is possible that these encouraging results could be further improved by using non-histogram mutual information estimators, like k-Nearest Neighbor or Kernel-Density estimators, but for short (<1000 points) and irregularly sampled datasets the proposed algorithm is already a great improvement.

Comparison of adverse effects of proton and X-ray chemoradiotherapy for esophageal cancer using an adaptive dose-volume histogram analysis.

PubMed

Makishima, Hirokazu; Ishikawa, Hitoshi; Terunuma, Toshiyuki; Hashimoto, Takayuki; Yamanashi, Koichi; Sekiguchi, Takao; Mizumoto, Masashi; Okumura, Toshiyuki; Sakae, Takeji; Sakurai, Hideyuki

2015-05-01

Cardiopulmonary late toxicity is of concern in concurrent chemoradiotherapy (CCRT) for esophageal cancer. The aim of this study was to examine the benefit of proton beam therapy (PBT) using clinical data and adaptive dose-volume histogram (DVH) analysis. The subjects were 44 patients with esophageal cancer who underwent definitive CCRT using X-rays (n = 19) or protons (n = 25). Experimental recalculation using protons was performed for the patient actually treated with X-rays, and vice versa. Target coverage and dose constraints of normal tissues were conserved. Lung V5-V20, mean lung dose (MLD), and heart V30-V50 were compared for risk organ doses between experimental plans and actual treatment plans. Potential toxicity was estimated using protons in patients actually treated with X-rays, and vice versa. Pulmonary events of Grade ≥2 occurred in 8/44 cases (18%), and cardiac events were seen in 11 cases (25%). Risk organ doses in patients with events of Grade ≥2 were significantly higher than for those with events of Grade ≤1. Risk organ doses were lower in proton plans compared with X-ray plans. All patients suffering toxicity who were treated with X-rays (n = 13) had reduced predicted doses in lung and heart using protons, while doses in all patients treated with protons (n = 24) with toxicity of Grade ≤1 had worsened predicted toxicity with X-rays. Analysis of normal tissue complication probability showed a potential reduction in toxicity by using proton beams. Irradiation dose, volume and adverse effects on the heart and lung can be reduced using protons. Thus, PBT is a promising treatment modality for the management of esophageal cancer. © The Author 2015. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

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

Understanding Large-scale Structure in the SSA22 Protocluster Region Using Cosmological Simulations

NASA Astrophysics Data System (ADS)

Topping, Michael W.; Shapley, Alice E.; Steidel, Charles C.; Naoz, Smadar; Primack, Joel R.

2018-01-01

We investigate the nature and evolution of large-scale structure within the SSA22 protocluster region at z = 3.09 using cosmological simulations. A redshift histogram constructed from current spectroscopic observations of the SSA22 protocluster reveals two separate peaks at z = 3.065 (blue) and z = 3.095 (red). Based on these data, we report updated overdensity and mass calculations for the SSA22 protocluster. We find {δ }b,{gal}=4.8+/- 1.8 and {δ }r,{gal}=9.5+/- 2.0 for the blue and red peaks, respectively, and {δ }t,{gal}=7.6+/- 1.4 for the entire region. These overdensities correspond to masses of {M}b=(0.76+/- 0.17)× {10}15{h}-1 {M}ȯ , {M}r=(2.15+/- 0.32)× {10}15{h}-1 {M}ȯ , and {M}t=(3.19+/- 0.40)× {10}15{h}-1 {M}ȯ for the red, blue, and total peaks, respectively. We use the Small MultiDark Planck (SMDPL) simulation to identify comparably massive z∼ 3 protoclusters, and uncover the underlying structure and ultimate fate of the SSA22 protocluster. For this analysis, we construct mock redshift histograms for each simulated z∼ 3 protocluster, quantitatively comparing them with the observed SSA22 data. We find that the observed double-peaked structure in the SSA22 redshift histogram corresponds not to a single coalescing cluster, but rather the proximity of a ∼ {10}15{h}-1 {M}ȯ protocluster and at least one > {10}14{h}-1 {M}ȯ cluster progenitor. Such associations in the SMDPL simulation are easily understood within the framework of hierarchical clustering of dark matter halos. We finally find that the opportunity to observe such a phenomenon is incredibly rare, with an occurrence rate of 7.4{h}3 {{{Gpc}}}-3. Based on data obtained at the W.M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration, and was made possible by the generous financial support of the W.M. Keck Foundation.

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.

Liquid-liquid transition in the ST2 model of water

NASA Astrophysics Data System (ADS)

Debenedetti, Pablo

2013-03-01

We present clear evidence of the existence of a metastable liquid-liquid phase transition in the ST2 model of water. Using four different techniques (the weighted histogram analysis method with single-particle moves, well-tempered metadynamics with single-particle moves, weighted histograms with parallel tempering and collective particle moves, and conventional molecular dynamics), we calculate the free energy surface over a range of thermodynamic conditions, we perform a finite size scaling analysis for the free energy barrier between the coexisting liquid phases, we demonstrate the attainment of diffusive behavior, and we perform stringent thermodynamic consistency checks. The results provide conclusive evidence of a first-order liquid-liquid transition. We also show that structural equilibration in the sluggish low-density phase is attained over the time scale of our simulations, and that crystallization times are significantly longer than structural equilibration, even under deeply supercooled conditions. We place our results in the context of the theory of metastability.

Enhancement of low visibility aerial images using histogram truncation and an explicit Retinex representation for balancing contrast and color consistency

NASA Astrophysics Data System (ADS)

Liu, Changjiang; Cheng, Irene; Zhang, Yi; Basu, Anup

2017-06-01

This paper presents an improved multi-scale Retinex (MSR) based enhancement for ariel images under low visibility. For traditional multi-scale Retinex, three scales are commonly employed, which limits its application scenarios. We extend our research to a general purpose enhanced method, and design an MSR with more than three scales. Based on the mathematical analysis and deductions, an explicit multi-scale representation is proposed that balances image contrast and color consistency. In addition, a histogram truncation technique is introduced as a post-processing strategy to remap the multi-scale Retinex output to the dynamic range of the display. Analysis of experimental results and comparisons with existing algorithms demonstrate the effectiveness and generality of the proposed method. Results on image quality assessment proves the accuracy of the proposed method with respect to both objective and subjective criteria.

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.

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.

On the equivalence of the RTI and SVM approaches to time correlated analysis

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

Croft, S.; Favalli, A.; Henzlova, D.

2014-11-21

Recently two papers on how to perform passive neutron auto-correlation analysis on time gated histograms formed from pulse train data, generically called time correlation analysis (TCA), have appeared in this journal [1,2]. For those of us working in international nuclear safeguards these treatments are of particular interest because passive neutron multiplicity counting is a widely deployed technique for the quantification of plutonium. The purpose of this letter is to show that the skewness-variance-mean (SVM) approach developed in [1] is equivalent in terms of assay capability to the random trigger interval (RTI) analysis laid out in [2]. Mathematically we could alsomore » use other numerical ways to extract the time correlated information from the histogram data including for example what we might call the mean, mean square, and mean cube approach. The important feature however, from the perspective of real world applications, is that the correlated information extracted is the same, and subsequently gets interpreted in the same way based on the same underlying physics model.« less

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.

Offset Printing Plate Quality Sensor on a Low-Cost Processor

PubMed Central

Poljak, Jelena; Botella, Guillermo; García, Carlos; Poljaček, Sanja Mahović; Prieto-Matías, Manuel; Tirado, Francisco

2013-01-01

The aim of this work is to develop a microprocessor-based sensor that measures the quality of the offset printing plate through the introduction of different image analysis applications. The main features of the presented system are the low cost, the low amount of power consumption, its modularity and easy integration with other industrial modules for printing plates, and its robustness against noise environments. For the sake of clarity, a viability analysis of previous software is presented through different strategies, based on dynamic histogram and Hough transform. This paper provides performance and scalability data compared with existing costly commercial devices. Furthermore, a general overview of quality control possibilities for printing plates is presented and could be useful to a system where such controls are regularly conducted. PMID:24284766

Brain Tissue PO2 Measurement During Normoxia and Hypoxia Using Two-Photon Phosphorescence Lifetime Microscopy.

PubMed

Xu, Kui; Boas, David A; Sakadžić, Sava; LaManna, Joseph C

2017-01-01

Key to the understanding of the principles of physiological and structural acclimatization to changes in the balance between energy supply (represented by substrate and oxygen delivery, and mitochondrial oxidative phosphorylation) and energy demand (initiated by neuronal activity) is to determine the controlling variables, how they are sensed and the mechanisms initiated to maintain the balance. The mammalian brain depends completely on continuous delivery of oxygen to maintain its function. We hypothesized that tissue oxygen is the primary sensed variable. In this study two-photon phosphorescence lifetime microscopy (2PLM) was used to determine and define the tissue oxygen tension field within the cerebral cortex of mice to a cortical depth of between 200-250 μm under normoxia and acute hypoxia (FiO 2  = 0.10). High-resolution images can provide quantitative distributions of oxygen and intercapillary oxygen gradients. The data are best appreciated by quantifying the distribution histogram that can then be used for analysis. For example, in the brain cortex of a mouse, at a depth of 200 μm, tissue oxygen tension was mapped and the distribution histogram was compared under normoxic and mild hypoxic conditions. This powerful method can provide for the first time a description of the delivery and availability of brain oxygen in vivo.

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…

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)

CERESVis: A QC Tool for CERES that Leverages Browser Technology for Data Validation

NASA Astrophysics Data System (ADS)

Chu, C.; Sun-Mack, S.; Heckert, E.; Chen, Y.; Doelling, D.

2015-12-01

In this poster, we are going to present three user interfaces that CERES team uses to validate pixel-level data. Besides our home grown tools, we will aslo present the browser technology that we use to provide interactive interfaces, such as jquery, HighCharts and Google Earth. We pass data to the users' browsers and use the browsers to do some simple computations. The three user interfaces are: Thumbnails -- it displays hundrends images to allow users to browse 24-hour data files in few seconds. Multiple-synchronized cursors -- it allows users to compare multiple images side by side. Bounding Boxes and Histograms -- it allows users to draw multiple bounding boxes on an image and the browser computes/display the histograms.

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.

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.

Spline smoothing of histograms by linear programming

NASA Technical Reports Server (NTRS)

Bennett, J. O.

1972-01-01

An algorithm for an approximating function to the frequency distribution is obtained from a sample of size n. To obtain the approximating function a histogram is made from the data. Next, Euclidean space approximations to the graph of the histogram using central B-splines as basis elements are obtained by linear programming. The approximating function has area one and is nonnegative.

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.

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.

Improved image retrieval based on fuzzy colour feature vector

NASA Astrophysics Data System (ADS)

Ben-Ahmeida, Ahlam M.; Ben Sasi, Ahmed Y.

2013-03-01

One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.

Multi-scale Morphological Image Enhancement of Chest Radiographs by a Hybrid Scheme.

PubMed

Alavijeh, Fatemeh Shahsavari; Mahdavi-Nasab, Homayoun

2015-01-01

Chest radiography is a common diagnostic imaging test, which contains an enormous amount of information about a patient. However, its interpretation is highly challenging. The accuracy of the diagnostic process is greatly influenced by image processing algorithms; hence enhancement of the images is indispensable in order to improve visibility of the details. This paper aims at improving radiograph parameters such as contrast, sharpness, noise level, and brightness to enhance chest radiographs, making use of a triangulation method. Here, contrast limited adaptive histogram equalization technique and noise suppression are simultaneously performed in wavelet domain in a new scheme, followed by morphological top-hat and bottom-hat filtering. A unique implementation of morphological filters allows for adjustment of the image brightness and significant enhancement of the contrast. The proposed method is tested on chest radiographs from Japanese Society of Radiological Technology database. The results are compared with conventional enhancement techniques such as histogram equalization, contrast limited adaptive histogram equalization, Retinex, and some recently proposed methods to show its strengths. The experimental results reveal that the proposed method can remarkably improve the image contrast while keeping the sensitive chest tissue information so that radiologists might have a more precise interpretation.

Multi-scale Morphological Image Enhancement of Chest Radiographs by a Hybrid Scheme

PubMed Central

Alavijeh, Fatemeh Shahsavari; Mahdavi-Nasab, Homayoun

2015-01-01

Chest radiography is a common diagnostic imaging test, which contains an enormous amount of information about a patient. However, its interpretation is highly challenging. The accuracy of the diagnostic process is greatly influenced by image processing algorithms; hence enhancement of the images is indispensable in order to improve visibility of the details. This paper aims at improving radiograph parameters such as contrast, sharpness, noise level, and brightness to enhance chest radiographs, making use of a triangulation method. Here, contrast limited adaptive histogram equalization technique and noise suppression are simultaneously performed in wavelet domain in a new scheme, followed by morphological top-hat and bottom-hat filtering. A unique implementation of morphological filters allows for adjustment of the image brightness and significant enhancement of the contrast. The proposed method is tested on chest radiographs from Japanese Society of Radiological Technology database. The results are compared with conventional enhancement techniques such as histogram equalization, contrast limited adaptive histogram equalization, Retinex, and some recently proposed methods to show its strengths. The experimental results reveal that the proposed method can remarkably improve the image contrast while keeping the sensitive chest tissue information so that radiologists might have a more precise interpretation. PMID:25709942

Using an image-extended relational database to support content-based image retrieval in a PACS.

PubMed

Traina, Caetano; Traina, Agma J M; Araújo, Myrian R B; Bueno, Josiane M; Chino, Fabio J T; Razente, Humberto; Azevedo-Marques, Paulo M

2005-12-01

This paper presents a new Picture Archiving and Communication System (PACS), called cbPACS, which has content-based image retrieval capabilities. The cbPACS answers range and k-nearest- neighbor similarity queries, employing a relational database manager extended to support images. The images are compared through their features, which are extracted by an image-processing module and stored in the extended relational database. The database extensions were developed aiming at efficiently answering similarity queries by taking advantage of specialized indexing methods. The main concept supporting the extensions is the definition, inside the relational manager, of distance functions based on features extracted from the images. An extension to the SQL language enables the construction of an interpreter that intercepts the extended commands and translates them to standard SQL, allowing any relational database server to be used. By now, the system implemented works on features based on color distribution of the images through normalized histograms as well as metric histograms. Metric histograms are invariant regarding scale, translation and rotation of images and also to brightness transformations. The cbPACS is prepared to integrate new image features, based on texture and shape of the main objects in the image.

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.

Convolution Comparison Pattern: An Efficient Local Image Descriptor for Fingerprint Liveness Detection

PubMed Central

Gottschlich, Carsten

2016-01-01

We present a new type of local image descriptor which yields binary patterns from small image patches. For the application to fingerprint liveness detection, we achieve rotation invariant image patches by taking the fingerprint segmentation and orientation field into account. We compute the discrete cosine transform (DCT) for these rotation invariant patches and attain binary patterns by comparing pairs of two DCT coefficients. These patterns are summarized into one or more histograms per image. Each histogram comprises the relative frequencies of pattern occurrences. Multiple histograms are concatenated and the resulting feature vector is used for image classification. We name this novel type of descriptor convolution comparison pattern (CCP). Experimental results show the usefulness of the proposed CCP descriptor for fingerprint liveness detection. CCP outperforms other local image descriptors such as LBP, LPQ and WLD on the LivDet 2013 benchmark. The CCP descriptor is a general type of local image descriptor which we expect to prove useful in areas beyond fingerprint liveness detection such as biological and medical image processing, texture recognition, face recognition and iris recognition, liveness detection for face and iris images, and machine vision for surface inspection and material classification. PMID:26844544

Fluorescence lifetime imaging ophthalmoscopy in type 2 diabetic patients who have no signs of diabetic retinopathy

NASA Astrophysics Data System (ADS)

Schweitzer, Dietrich; Deutsch, Lydia; Klemm, Matthias; Jentsch, Susanne; Hammer, Martin; Peters, Sven; Haueisen, Jens; Müller, Ulrich A.; Dawczynski, Jens

2015-06-01

The time-resolved autofluorescence of the eye is used for the detection of metabolic alteration in diabetic patients who have no signs of diabetic retinopathy. One eye from 37 phakic and 11 pseudophakic patients with type 2 diabetes, and one eye from 25 phakic and 23 pseudophakic healthy subjects were included in the study. After a three-exponential fit of the decay of autofluorescence, histograms of lifetimes τi, amplitudes αi, and relative contributions Qi were statistically compared between corresponding groups in two spectral channels (490450 ps, and the shift of τ3 from ˜3000 to 3700 ps in ch1 of diabetic patients when compared with healthy subjects indicate an increased production of free flavin adenine dinucleotide, accumulation of advanced glycation end products (AGE), and, probably, a change from free to protein-bound reduced nicotinamide adenine dinucleotide at the fundus. AGE also accumulated in the crystalline lens.

Fluorescence lifetime imaging ophthalmoscopy in type 2 diabetic patients who have no signs of diabetic retinopathy.

PubMed

Schweitzer, Dietrich; Deutsch, Lydia; Klemm, Matthias; Jentsch, Susanne; Hammer, Martin; Peters, Sven; Haueisen, Jens; Müller, Ulrich A; Dawczynski, Jens

2015-06-01

The time-resolved autofluorescence of the eye is used for the detection of metabolic alteration in diabetic patients who have no signs of diabetic retinopathy. One eye from 37 phakic and 11 pseudophakic patients with type 2 diabetes, and one eye from 25 phakic and 23 pseudophakic healthy subjects were included n the study. After a three-exponential fit of the decay of autofluorescence, histograms of lifetimes τ(i), amplitudes α(i), and relative contributions Q(i) were statistically compared between corresponding groups in two spectral channels (490 < ch1 < 560 nm, 560 < ch2 < 700 nm). The change in single fluorophores was estimated by applying the Holm–Bonferroni method and by calculating differences in the sum histograms of lifetimes. Median and mean of the histograms of τ(2), τ(3), and α(3) in ch1 show the greatest differences between phakic diabetic patients and age-matched controls (p < 0.000004). The lack of pixels with a τ(2) of ∼360 ps, the increased number of pixels with τ(2) > 450 ps, and the shift of τ(3) from ∼3000 to 3700 ps in ch1 of diabetic patients when compared with healthy subjects indicate an increased production of free flavin adenine dinucleotide, accumulation of advanced glycation end products (AGE), and, probably, a change from free to protein-bound reduced nicotinamide adenine inucleotide at the fundus. AGE also accumulated in the crystalline lens.

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

Tucker, Susan L.; Liu, H. Helen; Wang, Shulian

Purpose: The aim of this study was to investigate the effect of radiation dose distribution in the lung on the risk of postoperative pulmonary complications among esophageal cancer patients. Methods and Materials: We analyzed data from 110 patients with esophageal cancer treated with concurrent chemoradiotherapy followed by surgery at our institution from 1998 to 2003. The endpoint for analysis was postsurgical pneumonia or acute respiratory distress syndrome. Dose-volume histograms (DVHs) and dose-mass histograms (DMHs) for the whole lung were used to fit normal-tissue complication probability (NTCP) models, and the quality of fits were compared using bootstrap analysis. Results: Normal-tissue complicationmore » probability modeling identified that the risk of postoperative pulmonary complications was most significantly associated with small absolute volumes of lung spared from doses {>=}5 Gy (VS5), that is, exposed to doses <5 Gy. However, bootstrap analysis found no significant difference between the quality of this model and fits based on other dosimetric parameters, including mean lung dose, effective dose, and relative volume of lung receiving {>=}5 Gy, probably because of correlations among these factors. The choice of DVH vs. DMH or the use of fractionation correction did not significantly affect the results of the NTCP modeling. The parameter values estimated for the Lyman NTCP model were as follows (with 95% confidence intervals in parentheses): n = 1.85 (0.04, {infinity}), m = 0.55 (0.22, 1.02), and D {sub 5} = 17.5 Gy (9.4 Gy, 102 Gy). Conclusions: In this cohort of esophageal cancer patients, several dosimetric parameters including mean lung dose, effective dose, and absolute volume of lung receiving <5 Gy provided similar descriptions of the risk of postoperative pulmonary complications as a function of Radiation dose distribution in the lung.« less

Choosing the best image processing method for masticatory performance assessment when using two-coloured specimens.

PubMed

Vaccaro, G; Pelaez, J I; Gil, J A

2016-07-01

Objective masticatory performance assessment using two-coloured specimens relies on image processing techniques; however, just a few approaches have been tested and no comparative studies are reported. The aim of this study was to present a selection procedure of the optimal image analysis method for masticatory performance assessment with a given two-coloured chewing gum. Dentate participants (n = 250; 25 ± 6·3 years) chewed red-white chewing gums for 3, 6, 9, 12, 15, 18, 21 and 25 cycles (2000 samples). Digitalised images of retrieved specimens were analysed using 122 image processing methods (IPMs) based on feature extraction algorithms (pixel values and histogram analysis). All IPMs were tested following the criteria of: normality of measurements (Kolmogorov-Smirnov), ability to detect differences among mixing states (anova corrected with post hoc Bonferroni) and moderate-to-high correlation with the number of cycles (Spearman's Rho). The optimal IPM was chosen using multiple criteria decision analysis (MCDA). Measurements provided by all IPMs proved to be normally distributed (P < 0·05), 116 proved sensible to mixing states (P < 0·05), and 35 showed moderate-to-high correlation with the number of cycles (|ρ| > 0·5; P < 0·05). The variance of the histogram of the Hue showed the highest correlation with the number of cycles (ρ = 0·792; P < 0·0001) and the highest MCDA score (optimal). The proposed procedure proved to be reliable and able to select the optimal approach among multiple IPMs. This experiment may be reproduced to identify the optimal approach for each case of locally available test foods. © 2016 John Wiley & Sons Ltd.

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis

PubMed Central

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine

2018-01-01

Background Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. Objective The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. Methods The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Results Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. Conclusions MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians’ skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. PMID:29720361

External Beam Radiotherapy for Prostate Cancer Patients on Anticoagulation Therapy: How Significant is the Bleeding Toxicity?

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

Choe, Kevin S.; Jani, Ashesh B.; Liauw, Stanley L., E-mail: sliauw@radonc.uchicago.ed

Purpose: To characterize the bleeding toxicity associated with external beam radiotherapy for prostate cancer patients receiving anticoagulation (AC) therapy. Methods and Materials: The study cohort consisted of 568 patients with adenocarcinoma of the prostate who were treated with definitive external beam radiotherapy. Of these men, 79 were receiving AC therapy with either warfarin or clopidogrel. All patients were treated with three-dimensional conformal radiotherapy or intensity-modulated radiotherapy. Bleeding complications were recorded during treatment and subsequent follow-up visits. Results: With a median follow-up of 48 months, the 4-year actuarial risk of Grade 3 or worse bleeding toxicity was 15.5% for those receivingmore » AC therapy compared with 3.6% among those not receiving AC (p < .0001). On multivariate analysis, AC therapy was the only significant factor associated with Grade 3 or worse bleeding (p < .0001). For patients taking AC therapy, the crude rate of bleeding was 39.2%. Multivariate analysis within the AC group demonstrated that a higher radiotherapy dose (p = .0408), intensity-modulated radiotherapy (p = 0.0136), and previous transurethral resection of the prostate (p = .0001) were associated with Grade 2 or worse bleeding toxicity. Androgen deprivation therapy was protective against bleeding, with borderline significance (p = 0.0599). Dose-volume histogram analysis revealed that Grade 3 or worse bleeding was minimized if the percentage of the rectum receiving >=70 Gy was <10% or the rectum receiving >=50 Gy was <50%. Conclusion: Patients taking AC therapy have a substantial risk of bleeding toxicity from external beam radiotherapy. In this setting, dose escalation or intensity-modulated radiotherapy should be used judiciously. With adherence to strict dose-volume histogram criteria and minimizing hotspots, the risk of severe bleeding might be reduced.« less

[Automatic analysis of the interference EMG of the brachioradial muscle in neuropathy of the radial nerve].

PubMed

Popelianskiĭ, Ia Iu; Bogdanov, E I; Khamidullina, V Z

1988-01-01

In 8 patients with radial neuropathy the authors studied histograms of distribution of potentials of motor units (PMU) by their duration, as well as of the number of intercrossings (T) and the mean amplitude of interference EMG of the musculus brachioradialis. The findings included a decrease in the T value and T/M ratio in the presence of an insignificant shift of the histograms and of the mean duration of PMU. With regard to the diagnosis of early neuropathies a reduction in the average value of T and T/M in the presence of ungraded voluntary tension of the muscle is diagnostically more important than changes in the duration of individual PMU.

Graphical and Numerical Descriptive Analysis: Exploratory Tools Applied to Vietnamese Data

ERIC Educational Resources Information Center

Haughton, Dominique; Phong, Nguyen

2004-01-01

This case study covers several exploratory data analysis ideas, the histogram and boxplot, kernel density estimates, the recently introduced bagplot--a two-dimensional extension of the boxplot--as well as the violin plot, which combines a boxplot with a density shape plot. We apply these ideas and demonstrate how to interpret the output from these…

NASA TLA workload analysis support. Volume 3: FFD autopilot scenario validation data

NASA Technical Reports Server (NTRS)

Sundstrom, J. L.

1980-01-01

The data used to validate a seven time line analysis of forward flight deck autopilot mode for the pilot and copilot for NASA B737 terminal configured vehicle are presented. Demand workloads are given in two forms: workload histograms and workload summaries (bar graphs). A report showing task length and task interaction is also presented.

Morphologic Features of Magnetic Resonance Imaging as a Surrogate of Capsular Contracture in Breast Cancer Patients With Implant-based Reconstructions.

PubMed

Tyagi, Neelam; Sutton, Elizabeth; Hunt, Margie; Zhang, Jing; Oh, Jung Hun; Apte, Aditya; Mechalakos, James; Wilgucki, Molly; Gelb, Emily; Mehrara, Babak; Matros, Evan; Ho, Alice

2017-02-01

Capsular contracture (CC) is a serious complication in patients receiving implant-based reconstruction for breast cancer. Currently, no objective methods are available for assessing CC. The goal of the present study was to identify image-based surrogates of CC using magnetic resonance imaging (MRI). We analyzed a retrospective data set of 50 patients who had undergone both a diagnostic MRI scan and a plastic surgeon's evaluation of the CC score (Baker's score) within a 6-month period after mastectomy and reconstructive surgery. The MRI scans were assessed for morphologic shape features of the implant and histogram features of the pectoralis muscle. The shape features, such as roundness, eccentricity, solidity, extent, and ratio length for the implant, were compared with the Baker score. For the pectoralis muscle, the muscle width and median, skewness, and kurtosis of the intensity were compared with the Baker score. Univariate analysis (UVA) using a Wilcoxon rank-sum test and multivariate analysis with the least absolute shrinkage and selection operator logistic regression was performed to determine significant differences in these features between the patient groups categorized according to their Baker's scores. UVA showed statistically significant differences between grade 1 and grade ≥2 for morphologic shape features and histogram features, except for volume and skewness. Only eccentricity, ratio length, and volume were borderline significant in differentiating grade ≤2 and grade ≥3. Features with P<.1 on UVA were used in the multivariate least absolute shrinkage and selection operator logistic regression analysis. Multivariate analysis showed a good level of predictive power for grade 1 versus grade ≥2 CC (area under the receiver operating characteristic curve 0.78, sensitivity 0.78, and specificity 0.82) and for grade ≤2 versus grade ≥3 CC (area under the receiver operating characteristic curve 0.75, sensitivity 0.75, and specificity 0.79). The morphologic shape features described on MR images were associated with the severity of CC. MRI has the potential to further improve the diagnostic ability of the Baker score in breast cancer patients who undergo implant reconstruction. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

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.

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

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.

Automated Counting of Particles To Quantify Cleanliness

NASA Technical Reports Server (NTRS)

Rhode, James

2005-01-01

A machine vision system, similar to systems used in microbiological laboratories to count cultured microbes, has been proposed for quantifying the cleanliness of nominally precisely cleaned hardware by counting residual contaminant particles. The system would include a microscope equipped with an electronic camera and circuitry to digitize the camera output, a personal computer programmed with machine-vision and interface software, and digital storage media. A filter pad, through which had been aspirated solvent from rinsing the hardware in question, would be placed on the microscope stage. A high-resolution image of the filter pad would be recorded. The computer would analyze the image and present a histogram of sizes of particles on the filter. On the basis of the histogram and a measure of the desired level of cleanliness, the hardware would be accepted or rejected. If the hardware were accepted, the image would be saved, along with other information, as a quality record. If the hardware were rejected, the histogram and ancillary information would be recorded for analysis of trends. The software would perceive particles that are too large or too numerous to meet a specified particle-distribution profile. Anomalous particles or fibrous material would be flagged for inspection.

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.

Unsupervised spike sorting based on discriminative subspace learning.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2014-01-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.

"Textural analysis of multiparametric MRI detects transition zone prostate cancer".

PubMed

Sidhu, Harbir S; Benigno, Salvatore; Ganeshan, Balaji; Dikaios, Nikos; Johnston, Edward W; Allen, Clare; Kirkham, Alex; Groves, Ashley M; Ahmed, Hashim U; Emberton, Mark; Taylor, Stuart A; Halligan, Steve; Punwani, Shonit

2017-06-01

To evaluate multiparametric-MRI (mpMRI) derived histogram textural-analysis parameters for detection of transition zone (TZ) prostatic tumour. Sixty-seven consecutive men with suspected prostate cancer underwent 1.5T mpMRI prior to template-mapping-biopsy (TPM). Twenty-six men had 'significant' TZ tumour. Two radiologists in consensus matched TPM to the single axial slice best depicting tumour, or largest TZ diameter for those with benign histology, to define single-slice whole TZ-regions-of-interest (ROIs). Textural-parameter differences between single-slice whole TZ-ROI containing significant tumour versus benign/insignificant tumour were analysed using Mann Whitney U test. Diagnostic accuracy was assessed by receiver operating characteristic area under curve (ROC-AUC) analysis cross-validated with leave-one-out (LOO) analysis. ADC kurtosis was significantly lower (p < 0.001) in TZ containing significant tumour with ROC-AUC 0.80 (LOO-AUC 0.78); the difference became non-significant following exclusion of significant tumour from single-slice whole TZ-ROI (p = 0.23). T1-entropy was significantly lower (p = 0.004) in TZ containing significant tumour with ROC-AUC 0.70 (LOO-AUC 0.66) and was unaffected by excluding significant tumour from TZ-ROI (p = 0.004). Combining these parameters yielded ROC-AUC 0.86 (LOO-AUC 0.83). Textural features of the whole prostate TZ can discriminate significant prostatic cancer through reduced kurtosis of the ADC-histogram where significant tumour is included in TZ-ROI and reduced T1 entropy independent of tumour inclusion. • MR textural features of prostate transition zone may discriminate significant prostatic cancer. • Transition zone (TZ) containing significant tumour demonstrates a less peaked ADC histogram. • TZ containing significant tumour reveals higher post-contrast T1-weighted homogeneity. • The utility of MR texture analysis in prostate cancer merits further investigation.

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

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

Andrews, M; Abazeed, M; Woody, N

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less

Statistical normalization techniques for magnetic resonance imaging.

PubMed

Shinohara, Russell T; Sweeney, Elizabeth M; Goldsmith, Jeff; Shiee, Navid; Mateen, Farrah J; Calabresi, Peter A; Jarso, Samson; Pham, Dzung L; Reich, Daniel S; Crainiceanu, Ciprian M

2014-01-01

While computed tomography and other imaging techniques are measured in absolute units with physical meaning, magnetic resonance images are expressed in arbitrary units that are difficult to interpret and differ between study visits and subjects. Much work in the image processing literature on intensity normalization has focused on histogram matching and other histogram mapping techniques, with little emphasis on normalizing images to have biologically interpretable units. Furthermore, there are no formalized principles or goals for the crucial comparability of image intensities within and across subjects. To address this, we propose a set of criteria necessary for the normalization of images. We further propose simple and robust biologically motivated normalization techniques for multisequence brain imaging that have the same interpretation across acquisitions and satisfy the proposed criteria. We compare the performance of different normalization methods in thousands of images of patients with Alzheimer's disease, hundreds of patients with multiple sclerosis, and hundreds of healthy subjects obtained in several different studies at dozens of imaging centers.

An efficient sequential approach to tracking multiple objects through crowds for real-time intelligent CCTV systems.

PubMed

Li, Liyuan; Huang, Weimin; Gu, Irene Yu-Hua; Luo, Ruijiang; Tian, Qi

2008-10-01

Efficiency and robustness are the two most important issues for multiobject tracking algorithms in real-time intelligent video surveillance systems. We propose a novel 2.5-D approach to real-time multiobject tracking in crowds, which is formulated as a maximum a posteriori estimation problem and is approximated through an assignment step and a location step. Observing that the occluding object is usually less affected by the occluded objects, sequential solutions for the assignment and the location are derived. A novel dominant color histogram (DCH) is proposed as an efficient object model. The DCH can be regarded as a generalized color histogram, where dominant colors are selected based on a given distance measure. Comparing with conventional color histograms, the DCH only requires a few color components (31 on average). Furthermore, our theoretical analysis and evaluation on real data have shown that DCHs are robust to illumination changes. Using the DCH, efficient implementations of sequential solutions for the assignment and location steps are proposed. The assignment step includes the estimation of the depth order for the objects in a dispersing group, one-by-one assignment, and feature exclusion from the group representation. The location step includes the depth-order estimation for the objects in a new group, the two-phase mean-shift location, and the exclusion of tracked objects from the new position in the group. Multiobject tracking results and evaluation from public data sets are presented. Experiments on image sequences captured from crowded public environments have shown good tracking results, where about 90% of the objects have been successfully tracked with the correct identification numbers by the proposed method. Our results and evaluation have indicated that the method is efficient and robust for tracking multiple objects (>or= 3) in complex occlusion for real-world surveillance scenarios.

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.

a Probability-Based Statistical Method to Extract Water Body of TM Images with Missing Information

NASA Astrophysics Data System (ADS)

Lian, Shizhong; Chen, Jiangping; Luo, Minghai

2016-06-01

Water information cannot be accurately extracted using TM images because true information is lost in some images because of blocking clouds and missing data stripes, thereby water information cannot be accurately extracted. Water is continuously distributed in natural conditions; thus, this paper proposed a new method of water body extraction based on probability statistics to improve the accuracy of water information extraction of TM images with missing information. Different disturbing information of clouds and missing data stripes are simulated. Water information is extracted using global histogram matching, local histogram matching, and the probability-based statistical method in the simulated images. Experiments show that smaller Areal Error and higher Boundary Recall can be obtained using this method compared with the conventional methods.

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

Font, Joan; Beckman, John E.; Fathi, Kambiz

In this Letter, we introduce a technique for finding resonance radii in a disk galaxy. We use a two-dimensional velocity field in H{alpha} emission obtained with Fabry-Perot interferometry, derive the classical rotation curve, and subtract it off, leaving a residual velocity map. As the streaming motions should reverse sign at corotation, we detect these reversals and plot them in a histogram against galactocentric radius, excluding points where the amplitude of the reversal is smaller than the measurement uncertainty. The histograms show well-defined peaks which we assume to occur at resonance radii, identifying corotations as the most prominent peaks corresponding tomore » the relevant morphological features of the galaxy (notably bars and spiral arm systems). We compare our results with published measurements on the same galaxies using other methods and different types of data.« less

Joint Improvised Explosive Device Defeat Organization

DTIC Science & Technology

2009-01-01

searches increased exponentially. Palantir . Developed to provide C-IED network analysts with a collaborative link analysis tool, Palantir is used for...share data between teams and between other link analysis applications. Palantir outputs portray linked nodal networks, histogram data, and timeline...views. During FY 2008, the Palantir system was accessed by over 160 people investigating IED networks. Analyses by these people supported over

Association of Chairmen of Departments of Physiology Analysis of Annual Questionnaire--1983/84.

ERIC Educational Resources Information Center

Physiologist, 1984

1984-01-01

Presents the full questionnaire sent to chairmen of physiology departments, with statistical data (grand totals and means per department) provided for each item on the questionnaire. Includes histograms of faculty salaries and data on departmental budgets and space. (JN)

Deviation from the mean in teaching uncertainties

NASA Astrophysics Data System (ADS)

Budini, N.; Giorgi, S.; Sarmiento, L. M.; Cámara, C.; Carreri, R.; Gómez Carrillo, S. C.

2017-07-01

In this work we present two simple and interactive web-based activities for introducing students to the concepts of uncertainties in measurements. These activities are based on the real-time construction of histograms from students measurements and their subsequent analysis through an active and dynamic approach.

MC-TESTER: a universal tool for comparisons of Monte Carlo predictions for particle decays in high energy physics

NASA Astrophysics Data System (ADS)

Golonka, P.; Pierzchała, T.; Waş, Z.

2004-02-01

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. Our test consists of two steps. Different Monte Carlo programs are run; events with decays of a chosen particle are searched, decay trees are analyzed and appropriate information is stored. Then, at the analysis step, a list of all found decay modes is defined and branching ratios are calculated for both runs. Histograms of all scalar Lorentz-invariant masses constructed from the decay products are plotted and compared for each decay mode found in both runs. For each plot a measure of the difference of the distributions is calculated and its maximal value over all histograms for each decay channel is printed in a summary table. As an example of MC-TESTER application, we include a test with the τ lepton decay Monte Carlo generators, TAUOLA and PYTHIA. The HEPEVT (or LUJETS) common block is used as exclusive source of information on the generated events. Program summaryTitle of the program:MC-TESTER, version 1.1 Catalogue identifier: ADSM Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSM Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer: PC, two Intel Xeon 2.0 GHz processors, 512MB RAM Operating system: Linux Red Hat 6.1, 7.2, and also 8.0 Programming language used:C++, FORTRAN77: gcc 2.96 or 2.95.2 (also 3.2) compiler suite with g++ and g77 Size of the package: 7.3 MB directory including example programs (2 MB compressed distribution archive), without ROOT libraries (additional 43 MB). No. of bytes in distributed program, including test data, etc.: 2 024 425 Distribution format: tar gzip file Additional disk space required: Depends on the analyzed particle: 40 MB in the case of τ lepton decays (30 decay channels, 594 histograms, 82-pages booklet). Keywords: particle physics, decay simulation, Monte Carlo methods, invariant mass distributions, programs comparison Nature of the physical 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, to check correctness of the installations or for discussion of uncertainties. Method of solution: A typical HEP Monte Carlo program stores the generated events in the event records such as 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. Restrictions on the complexity of the problem: For a list of limitations see Section 6. Typical running time: Varies substantially with the analyzed decay particle. 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; ? processing takes additionally 10 seconds. Generation step runs may be executed simultaneously on multi-processor machines. Accessibility: web page: http://cern.ch/Piotr.Golonka/MC/MC-TESTER e-mails: Piotr.Golonka@CERN.CH, T.Pierzchala@friend.phys.us.edu.pl, Zbigniew.Was@CERN.CH.

Diagnostic Performance of Mammographic Texture Analysis in the Differential Diagnosis of Benign and Malignant Breast Tumors.

PubMed

Li, Zhiming; Yu, Lan; Wang, Xin; Yu, Haiyang; Gao, Yuanxiang; Ren, Yande; Wang, Gang; Zhou, Xiaoming

2017-11-09

The purpose of this study was to investigate the diagnostic performance of mammographic texture analysis in the differential diagnosis of benign and malignant breast tumors. Digital mammography images were obtained from the Picture Archiving and Communication System at our institute. Texture features of mammographic images were calculated. Mann-Whitney U test was used to identify differences between the benign and malignant group. The receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of texture features. Significant differences of texture features of histogram, gray-level co-occurrence matrix (GLCM) and run length matrix (RLM) were found between the benign and malignant breast group (P < .05). The area under the ROC (AUROC) of histogram, GLCM, and RLM were 0.800, 0.787, and 0.761, with no differences between them (P > .05). The AUROCs of imaging-based diagnosis, texture analysis, and imaging-based diagnosis combined with texture analysis were 0.873, 0.863, and 0.961, respectively. When imaging-based diagnosis was combined with texture analysis, the AUROC was higher than that of imaging-based diagnosis or texture analysis (P < .05). Mammographic texture analysis is a reliable technique for differential diagnosis of benign and malignant breast tumors. Furthermore, the combination of imaging-based diagnosis and texture analysis can significantly improve diagnostic performance. Copyright © 2017 Elsevier Inc. All rights reserved.

Bennett's acceptance ratio and histogram analysis methods enhanced by umbrella sampling along a reaction coordinate in configurational space.

PubMed

Kim, Ilsoo; Allen, Toby W

2012-04-28

Free energy perturbation, a method for computing the free energy difference between two states, is often combined with non-Boltzmann biased sampling techniques in order to accelerate the convergence of free energy calculations. Here we present a new extension of the Bennett acceptance ratio (BAR) method by combining it with umbrella sampling (US) along a reaction coordinate in configurational space. In this approach, which we call Bennett acceptance ratio with umbrella sampling (BAR-US), the conditional histogram of energy difference (a mapping of the 3N-dimensional configurational space via a reaction coordinate onto 1D energy difference space) is weighted for marginalization with the associated population density along a reaction coordinate computed by US. This procedure produces marginal histograms of energy difference, from forward and backward simulations, with higher overlap in energy difference space, rendering free energy difference estimations using BAR statistically more reliable. In addition to BAR-US, two histogram analysis methods, termed Bennett overlapping histograms with US (BOH-US) and Bennett-Hummer (linear) least square with US (BHLS-US), are employed as consistency and convergence checks for free energy difference estimation by BAR-US. The proposed methods (BAR-US, BOH-US, and BHLS-US) are applied to a 1-dimensional asymmetric model potential, as has been used previously to test free energy calculations from non-equilibrium processes. We then consider the more stringent test of a 1-dimensional strongly (but linearly) shifted harmonic oscillator, which exhibits no overlap between two states when sampled using unbiased Brownian dynamics. We find that the efficiency of the proposed methods is enhanced over the original Bennett's methods (BAR, BOH, and BHLS) through fast uniform sampling of energy difference space via US in configurational space. We apply the proposed methods to the calculation of the electrostatic contribution to the absolute solvation free energy (excess chemical potential) of water. We then address the controversial issue of ion selectivity in the K(+) ion channel, KcsA. We have calculated the relative binding affinity of K(+) over Na(+) within a binding site of the KcsA channel for which different, though adjacent, K(+) and Na(+) configurations exist, ideally suited to these US-enhanced methods. Our studies demonstrate that the significant improvements in free energy calculations obtained using the proposed methods can have serious consequences for elucidating biological mechanisms and for the interpretation of experimental data.

Correlation Between Echinoidea Size and Threat Level

NASA Astrophysics Data System (ADS)

Bakshi, S.; Lee, A.; Heim, N.; Payne, J.

2017-12-01

Echinoidea (or sea urchins), are small, spiny, globular, animals that populate the seafloors of nearly the entire planet. Echinoidea have existed on Earth since the Ordovician period, and from their archaic origin there is much to be learned about the relationship between Echinoidea body size and how it affects the survivability of the individual. The goal of this project is to determine how Echinoidea dimensions such as body volume, area, and length compare across extinct and extant species by plotting Echinoidea data in R. We will use stratigraphic data as a source to find which species of sea urchin from our data is extinct. We will then create three sets of three histograms of the size data for each type of measurement. One set will include histograms for sea urchin length, area, and volume. The other set will include histograms for extinct sea urchin length, area, and volume. The last set will include histograms for extant sea urchin length, area, and volume. Our data showed that extant sea urchins had a larger size, and extinct sea urchins were smaller. Our length data showed that the average length of all sea urchins were 54.95791 mm, the average length of extinct sea urchins were 51.0337 mm, and the average length of extant sea urchins were 66.12774 mm. There is a generally increasing trend of size over time, except for a small outlier about 350 million years ago, where echinoderm extinction selected towards larger species and biovolume was abnormally high. Our data also showed that over the past 200 million years, echinoderm extinction selectivity drove slightly smaller sea urchins towards extinction, further supporting the idea that a larger size was and still is advantageous for echinoderms.

Investigating the Role of Global Histogram Equalization Technique for 99mTechnetium-Methylene diphosphonate Bone Scan Image Enhancement

PubMed Central

Pandey, Anil Kumar; Sharma, Param Dev; Dheer, Pankaj; Parida, Girish Kumar; Goyal, Harish; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-01-01

Purpose of the Study: 99mTechnetium-methylene diphosphonate (99mTc-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 99mTc-MDP-bone scan images. Materials and Methods: A set of 89 low contrast 99mTc-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. Results: 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. Conclusion: 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. PMID:29142344

The Utility of Using a Near-Infrared (NIR) Camera to Measure Beach Surface Moisture

NASA Astrophysics Data System (ADS)

Nelson, S.; Schmutz, P. P.

2017-12-01

Surface moisture content is an important factor that must be considered when studying aeolian sediment transport in a beach environment. A few different instruments and procedures are available for measuring surface moisture content (i.e. moisture probes, LiDAR, and gravimetric moisture data from surface scrapings); however, these methods can be inaccurate, costly, and inapplicable, particularly in the field. Near-infrared (NIR) spectral band imagery is another technique used to obtain moisture data. NIR imagery has been predominately used through remote sensing and has yet to be used for ground-based measurements. Dry sand reflects infrared radiation given off by the sun and wet sand absorbs IR radiation. All things considered, this study assesses the utility of measuring surface moisture content of beach sand with a modified NIR camera. A traditional point and shoot digital camera was internally modified with the placement of a visible light-blocking filter. Images were taken of three different types of beach sand at controlled moisture content values, with sunlight as the source of infrared radiation. A technique was established through trial and error by comparing resultant histogram values using Adobe Photoshop with the various moisture conditions. The resultant IR absorption histogram values were calibrated to actual gravimetric moisture content from surface scrapings of the samples. Overall, the results illustrate that the NIR spectrum modified camera does not provide the ability to adequately measure beach surface moisture content. However, there were noted differences in IR absorption histogram values among the different sediment types. Sediment with darker quartz mineralogy provided larger variations in histogram values, but the technique is not sensitive enough to accurately represent low moisture percentages, which are of most importance when studying aeolian sediment transport.

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.

CHOBS: Color Histogram of Block Statistics for Automatic Bleeding Detection in Wireless Capsule Endoscopy Video.

PubMed

Ghosh, Tonmoy; Fattah, Shaikh Anowarul; Wahid, Khan A

2018-01-01

Wireless capsule endoscopy (WCE) is the most advanced technology to visualize whole gastrointestinal (GI) tract in a non-invasive way. But the major disadvantage here, it takes long reviewing time, which is very laborious as continuous manual intervention is necessary. In order to reduce the burden of the clinician, in this paper, an automatic bleeding detection method for WCE video is proposed based on the color histogram of block statistics, namely CHOBS. A single pixel in WCE image may be distorted due to the capsule motion in the GI tract. Instead of considering individual pixel values, a block surrounding to that individual pixel is chosen for extracting local statistical features. By combining local block features of three different color planes of RGB color space, an index value is defined. A color histogram, which is extracted from those index values, provides distinguishable color texture feature. A feature reduction technique utilizing color histogram pattern and principal component analysis is proposed, which can drastically reduce the feature dimension. For bleeding zone detection, blocks are classified using extracted local features that do not incorporate any computational burden for feature extraction. From extensive experimentation on several WCE videos and 2300 images, which are collected from a publicly available database, a very satisfactory bleeding frame and zone detection performance is achieved in comparison to that obtained by some of the existing methods. In the case of bleeding frame detection, the accuracy, sensitivity, and specificity obtained from proposed method are 97.85%, 99.47%, and 99.15%, respectively, and in the case of bleeding zone detection, 95.75% of precision is achieved. The proposed method offers not only low feature dimension but also highly satisfactory bleeding detection performance, which even can effectively detect bleeding frame and zone in a continuous WCE video data.

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.

Brain early infarct detection using gamma correction extreme-level eliminating with weighting distribution.

PubMed

Teh, V; Sim, K S; Wong, E K

2016-11-01

According to the statistic from World Health Organization (WHO), stroke is one of the major causes of death globally. Computed tomography (CT) scan is one of the main medical diagnosis system used for diagnosis of ischemic stroke. CT scan provides brain images in Digital Imaging and Communication in Medicine (DICOM) format. The presentation of CT brain images is mainly relied on the window setting (window center and window width), which converts an image from DICOM format into normal grayscale format. Nevertheless, the ordinary window parameter could not deliver a proper contrast on CT brain images for ischemic stroke detection. In this paper, a new proposed method namely gamma correction extreme-level eliminating with weighting distribution (GCELEWD) is implemented to improve the contrast on CT brain images. GCELEWD is capable of highlighting the hypodense region for diagnosis of ischemic stroke. The performance of this new proposed technique, GCELEWD, is compared with four of the existing contrast enhancement technique such as brightness preserving bi-histogram equalization (BBHE), dualistic sub-image histogram equalization (DSIHE), extreme-level eliminating histogram equalization (ELEHE), and adaptive gamma correction with weighting distribution (AGCWD). GCELEWD shows better visualization for ischemic stroke detection and higher values with image quality assessment (IQA) module. SCANNING 38:842-856, 2016. © 2016 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

Uniform enhancement of optical micro-angiography images using Rayleigh contrast-limited adaptive histogram equalization.

PubMed

Yousefi, Siavash; Qin, Jia; Zhi, Zhongwei; Wang, Ruikang K

2013-02-01

Optical microangiography is an imaging technology that is capable of providing detailed functional blood flow maps within microcirculatory tissue beds in vivo. Some practical issues however exist when displaying and quantifying the microcirculation that perfuses the scanned tissue volume. These issues include: (I) Probing light is subject to specular reflection when it shines onto sample. The unevenness of the tissue surface makes the light energy entering the tissue not uniform over the entire scanned tissue volume. (II) The biological tissue is heterogeneous in nature, meaning the scattering and absorption properties of tissue would attenuate the probe beam. These physical limitations can result in local contrast degradation and non-uniform micro-angiogram images. In this paper, we propose a post-processing method that uses Rayleigh contrast-limited adaptive histogram equalization to increase the contrast and improve the overall appearance and uniformity of optical micro-angiograms without saturating the vessel intensity and changing the physical meaning of the micro-angiograms. The qualitative and quantitative performance of the proposed method is compared with those of common histogram equalization and contrast enhancement methods. We demonstrate that the proposed method outperforms other existing approaches. The proposed method is not limited to optical microangiography and can be used in other image modalities such as photo-acoustic tomography and scanning laser confocal microscopy.

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.

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.

Surface topography analysis and performance on post-CMP images (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lee, Jusang; Bello, Abner F.; Kakita, Shinichiro; Pieniazek, Nicholas; Johnson, Timothy A.

2017-03-01

Surface topography on post-CMP processing can be measured with white light interference microscopy to determine the planarity. Results are used to avoid under or over polishing and to decrease dishing. The numerical output of the surface topography is the RMS (root-mean-square) of the height. Beyond RMS, the topography image is visually examined and not further quantified. Subjective comparisons of the height maps are used to determine optimum CMP process conditions. While visual comparison of height maps can determine excursions, it's only through manual inspection of the images. In this work we describe methods of quantifying post-CMP surface topography characteristics that are used in other technical fields such as geography and facial-recognition. The topography image is divided into small surface patches of 7x7 pixels. Each surface patch is fitted to an analytic surface equation, in this case a third order polynomial, from which the gradient, directional derivatives, and other characteristics are calculated. Based on the characteristics, the surface patch is labeled as peak, ridge, flat, saddle, ravine, pit or hillside. The number of each label and thus the associated histogram is then used as a quantified characteristic of the surface topography, and could be used as a parameter for SPC (statistical process control) charting. In addition, the gradient for each surface patch is calculated, so the average, maximum, and other characteristics of the gradient distribution can be used for SPC. Repeatability measurements indicate high confidence where individual labels can be lower than 2% relative standard deviation. When the histogram is considered, an associated chi-squared value can be defined from which to compare other measurements. The chi-squared value of the histogram is a very sensitive and quantifiable parameter to determine the within wafer and wafer-to-wafer topography non-uniformity. As for the gradient histogram distribution, the chi-squared could again be calculated and used as yet another quantifiable parameter for SPC. In this work we measured the post Cu CMP of a die designed for 14nm technology. A region of interest (ROI) known to be indicative of the CMP processing is chosen for the topography analysis. The ROI, of size 1800 x 2500 pixels where each pixel represents 2um, was repeatably measured. We show the sensitivity based on measurements and the comparison between center and edge die measurements. The topography measurements and surface patch analysis were applied to hundreds of images representing the periodic process qualification runs required to control and verify CMP performance and tool matching. The analysis is shown to be sensitive to process conditions that vary in polishing time, type of slurry, CMP tool manufacturer, and CMP pad lifetime. Keywords: Keywords: CMP, Topography, Image Processing, Metrology, Interference microscopy, surface processing [1] De Lega, Xavier Colonna, and Peter De Groot. "Optical topography measurement of patterned wafers." Characterization and Metrology for ULSI Technology 2005 788 (2005): 432-436. [2] de Groot, Peter. "Coherence scanning interferometry." Optical Measurement of Surface Topography. Springer Berlin Heidelberg, 2011. 187-208. [3] Watson, Layne T., Thomas J. Laffey, and Robert M. Haralick. "Topographic classification of digital image intensity surfaces using generalized splines and the discrete cosine transformation." Computer Vision, Graphics, and Image Processing 29.2 (1985): 143-167. [4] Wang, Jun, et al. "3D facial expression recognition based on primitive surface feature distribution." Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on. Vol. 2. IEEE, 2006.

Numerically accurate computational techniques for optimal estimator analyses of multi-parameter models

NASA Astrophysics Data System (ADS)

Berger, Lukas; Kleinheinz, Konstantin; Attili, Antonio; Bisetti, Fabrizio; Pitsch, Heinz; Mueller, Michael E.

2018-05-01

Modelling unclosed terms in partial differential equations typically involves two steps: First, a set of known quantities needs to be specified as input parameters for a model, and second, a specific functional form needs to be defined to model the unclosed terms by the input parameters. Both steps involve a certain modelling error, with the former known as the irreducible error and the latter referred to as the functional error. Typically, only the total modelling error, which is the sum of functional and irreducible error, is assessed, but the concept of the optimal estimator enables the separate analysis of the total and the irreducible errors, yielding a systematic modelling error decomposition. In this work, attention is paid to the techniques themselves required for the practical computation of irreducible errors. Typically, histograms are used for optimal estimator analyses, but this technique is found to add a non-negligible spurious contribution to the irreducible error if models with multiple input parameters are assessed. Thus, the error decomposition of an optimal estimator analysis becomes inaccurate, and misleading conclusions concerning modelling errors may be drawn. In this work, numerically accurate techniques for optimal estimator analyses are identified and a suitable evaluation of irreducible errors is presented. Four different computational techniques are considered: a histogram technique, artificial neural networks, multivariate adaptive regression splines, and an additive model based on a kernel method. For multiple input parameter models, only artificial neural networks and multivariate adaptive regression splines are found to yield satisfactorily accurate results. Beyond a certain number of input parameters, the assessment of models in an optimal estimator analysis even becomes practically infeasible if histograms are used. The optimal estimator analysis in this paper is applied to modelling the filtered soot intermittency in large eddy simulations using a dataset of a direct numerical simulation of a non-premixed sooting turbulent flame.

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.

Converging stereotactic radiotherapy using kilovoltage X-rays: experimental irradiation of normal rabbit lung and dose-volume analysis with Monte Carlo simulation.

PubMed

Kawase, Takatsugu; Kunieda, Etsuo; Deloar, Hossain M; Tsunoo, Takanori; Seki, Satoshi; Oku, Yohei; Saitoh, Hidetoshi; Saito, Kimiaki; Ogawa, Eileen N; Ishizaka, Akitoshi; Kameyama, Kaori; Kubo, Atsushi

2009-10-01

To validate the feasibility of developing a radiotherapy unit with kilovoltage X-rays through actual irradiation of live rabbit lungs, and to explore the practical issues anticipated in future clinical application to humans through Monte Carlo dose simulation. A converging stereotactic irradiation unit was developed, consisting of a modified diagnostic computed tomography (CT) scanner. A tiny cylindrical volume in 13 normal rabbit lungs was individually irradiated with single fractional absorbed doses of 15, 30, 45, and 60 Gy. Observational CT scanning of the whole lung was performed every 2 weeks for 30 weeks after irradiation. After 30 weeks, histopathologic specimens of the lungs were examined. Dose distribution was simulated using the Monte Carlo method, and dose-volume histograms were calculated according to the data. A trial estimation of the effect of respiratory movement on dose distribution was made. A localized hypodense change and subsequent reticular opacity around the planning target volume (PTV) were observed in CT images of rabbit lungs. Dose-volume histograms of the PTVs and organs at risk showed a focused dose distribution to the target and sufficient dose lowering in the organs at risk. Our estimate of the dose distribution, taking respiratory movement into account, revealed dose reduction in the PTV. A converging stereotactic irradiation unit using kilovoltage X-rays was able to generate a focused radiobiologic reaction in rabbit lungs. Dose-volume histogram analysis and estimated sagittal dose distribution, considering respiratory movement, clarified the characteristics of the irradiation received from this type of unit.

Context-sensitive patch histograms for detecting rare events in histopathological data

NASA Astrophysics Data System (ADS)

Diaz, Kristians; Baust, Maximilian; Navab, Nassir

2017-03-01

Assessment of histopathological data is not only difficult due to its varying appearance, e.g. caused by staining artifacts, but also due to its sheer size: Common whole slice images feature a resolution of 6000x4000 pixels. Therefore, finding rare events in such data sets is a challenging and tedious task and developing sophisticated computerized tools is not easy, especially when no or little training data is available. In this work, we propose learning-free yet effective approach based on context sensitive patch-histograms in order to find extramedullary hematopoiesis events in Hematoxylin-Eosin-stained images. When combined with a simple nucleus detector, one can achieve performance levels in terms of sensitivity 0.7146, specificity 0.8476 and accuracy 0.8353 which are very well comparable to a recently published approach based on random forests.

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.

Climatological Study to Determine the Impact of Icing on the Low Level Windshear Alert System. Volume I. Analysis.

DOT National Transportation Integrated Search

1989-09-01

The climatological study was performed to determine the impact of icing on the performance of Low Level Windshear Alert System (LLWAS). : This report presents the icing statistical profile in the form of data tables and histograms of 106 LLWAS sites....

Univariate and Bivariate Loglinear Models for Discrete Test Score Distributions.

ERIC Educational Resources Information Center

Holland, Paul W.; Thayer, Dorothy T.

2000-01-01

Applied the theory of exponential families of distributions to the problem of fitting the univariate histograms and discrete bivariate frequency distributions that often arise in the analysis of test scores. Considers efficient computation of the maximum likelihood estimates of the parameters using Newton's Method and computationally efficient…

Asking the Right Questions: Techniques for Collaboration and School Change. 2nd Edition.

ERIC Educational Resources Information Center

Holcomb, Edie L.

This work provides school change leaders with tools, techniques, tips, examples, illustrations, and stories about promoting school change. Tools provided include histograms, surveys, run charts, weighted voting, force-field analysis, decision matrices, and many others. Chapter 1, "Introduction," applies a matrix for asking questions…

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.

Conductance Steamflow relationship

DOE Data Explorer

Whitney Trainor-Guitton

2015-04-01

These histograms represent our calibration of conductance of a volcanic geothermal field (with a clay cap) and the observed steam flow rates. See the following paper for further description: Trainor-Guitton, Hoversten,Nordquist, Intani, Value of information analysis using geothermal field data: accounting for multiple interpretations & determining new drilling locations. SEG Abstracts 2015.

Potential dosimetric benefit of dose-warping based 4D planning compared to conventional 3D planning in liver stereotactic body radiotherapy (SBRT)

NASA Astrophysics Data System (ADS)

Yeo, U. J.; Taylor, M. L.; Kron, T.; Pham, D.; Siva, S.; Franich, R. D.

2013-06-01

Respiratory motion induces dosimetric uncertainties for thoracic and abdominal cancer radiotherapy (RT) due to deforming and moving anatomy. This study investigates the extent of dosimetric differences between conventional 3D treatment planning and path-integrated 4D treatment planning in liver stereotactic body radiotherapy (SBRT). Respiratory-correlated 4DCT image sets with 10 phases were acquired for patients with liver tumours. Path-integrated 4D dose accumulation was performed using dose-warping techniques based on deformable image registration. Dose-volume histogram analysis demonstrated that the 3D planning approach overestimated doses to targets by up to 24% and underestimated dose to normal liver by ~4.5%, compared to the 4D planning methodology. Therefore, 4D planning has the potential to quantify such issues of under- and/or over-dosage and improve treatment accuracy.

Component Pin Recognition Using Algorithms Based on Machine Learning

NASA Astrophysics Data System (ADS)

Xiao, Yang; Hu, Hong; Liu, Ze; Xu, Jiangchang

2018-04-01

The purpose of machine vision for a plug-in machine is to improve the machine’s stability and accuracy, and recognition of the component pin is an important part of the vision. This paper focuses on component pin recognition using three different techniques. The first technique involves traditional image processing using the core algorithm for binary large object (BLOB) analysis. The second technique uses the histogram of oriented gradients (HOG), to experimentally compare the effect of the support vector machine (SVM) and the adaptive boosting machine (AdaBoost) learning meta-algorithm classifiers. The third technique is the use of an in-depth learning method known as convolution neural network (CNN), which involves identifying the pin by comparing a sample to its training. The main purpose of the research presented in this paper is to increase the knowledge of learning methods used in the plug-in machine industry in order to achieve better results.

Analysis of data acquired by Shuttle Imaging Radar SIR-A and Landsat Thematic Mapper over Baldwin County, Alabama

NASA Technical Reports Server (NTRS)

Wu, S.-T.

1985-01-01

Seasonally compatible data collected by SIR-A and by Landsat 4 TM over the lower coastal plain in Alabama were coregistered, forming a SIR-A/TM multichannel data set with 30 m x 30 m pixel size. Spectral signature plots and histogram analysis of the data were used to observe data characteristics. Radar returns from pine forest classes correlated highly with the tree ages, suggesting the potential utility of microwave remote sensing for forest biomass estimation. As compared with the TM-only data set, the use of SIR-A/TM data set improved classification accuracy of the seven land cover types studied. In addition, the SIR-A/TM classified data support previous finding by Engheta and Elachi (1982) that microwave data appear to be correlated with differing bottomland hardwood forest vegetation as associated with varying water regimens (i.e., wet versus dry).

Histogram of gradient and binarized statistical image features of wavelet subband-based palmprint features extraction

NASA Astrophysics Data System (ADS)

Attallah, Bilal; Serir, Amina; Chahir, Youssef; Boudjelal, Abdelwahhab

2017-11-01

Palmprint recognition systems are dependent on feature extraction. A method of feature extraction using higher discrimination information was developed to characterize palmprint images. In this method, two individual feature extraction techniques are applied to a discrete wavelet transform of a palmprint image, and their outputs are fused. The two techniques used in the fusion are the histogram of gradient and the binarized statistical image features. They are then evaluated using an extreme learning machine classifier before selecting a feature based on principal component analysis. Three palmprint databases, the Hong Kong Polytechnic University (PolyU) Multispectral Palmprint Database, Hong Kong PolyU Palmprint Database II, and the Delhi Touchless (IIDT) Palmprint Database, are used in this study. The study shows that our method effectively identifies and verifies palmprints and outperforms other methods based on feature extraction.

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)

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.

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).

Application of the Minkowski-functionals for automated pattern classification of breast parenchyma depicted by digital mammography

NASA Astrophysics Data System (ADS)

Boehm, Holger F.; Fischer, Tanja; Riosk, Dororthea; Britsch, Stefanie; Reiser, Maximilian

2008-03-01

With an estimated life-time-risk of about 10%, breast cancer is the most common cancer among women in western societies. Extensive mammography-screening programs have been implemented for diagnosis of the disease at an early stage. Several algorithms for computer-aided detection (CAD) have been proposed to help radiologists manage the increasing number of mammographic image-data and identify new cases of cancer. However, a major issue with most CAD-solutions is the fact that performance strongly depends on the structure and density of the breast tissue. Prior information about the global tissue quality in a patient would be helpful for selecting the most effective CAD-approach in order to increase the sensitivity of lesion-detection. In our study, we propose an automated method for textural evaluation of digital mammograms using the Minkowski Functionals in 2D. 80 mammograms are consensus-classified by two experienced readers as fibrosis, involution/atrophy, or normal. For each case, the topology of graylevel distribution is evaluated within a retromamillary image-section of 512 x 512 pixels. In addition, we obtain parameters from the graylevel-histogram (20th percentile, median and mean graylevel intensity). As a result, correct classification of the mammograms based on the densitometic parameters is achieved in between 38 and 48%, whereas topological analysis increases the rate to 83%. The findings demonstrate the effectiveness of the proposed algorithm. Compared to features obtained from graylevel histograms and comparable studies, we draw the conclusion that the presented method performs equally good or better. Our future work will be focused on the characterization of the mammographic tissue according to the Breast Imaging Reporting and Data System (BI-RADS). Moreover, other databases will be tested for an in-depth evaluation of the efficiency of our proposal.

Content Based Image Retrieval and Information Theory: A General Approach.

ERIC Educational Resources Information Center

Zachary, John; Iyengar, S. S.; Barhen, Jacob

2001-01-01

Proposes an alternative real valued representation of color based on the information theoretic concept of entropy. A theoretical presentation of image entropy is accompanied by a practical description of the merits and limitations of image entropy compared to color histograms. Results suggest that image entropy is a promising approach to image…

Scaling images using their background ratio. An application in statistical comparisons of images.

PubMed

Kalemis, A; Binnie, D; Bailey, D L; Flower, M A; Ott, R J

2003-06-07

Comparison of two medical images often requires image scaling as a pre-processing step. This is usually done with the scaling-to-the-mean or scaling-to-the-maximum techniques which, under certain circumstances, in quantitative applications may contribute a significant amount of bias. In this paper, we present a simple scaling method which assumes only that the most predominant values in the corresponding images belong to their background structure. The ratio of the two images to be compared is calculated and its frequency histogram is plotted. The scaling factor is given by the position of the peak in this histogram which belongs to the background structure. The method was tested against the traditional scaling-to-the-mean technique on simulated planar gamma-camera images which were compared using pixelwise statistical parametric tests. Both sensitivity and specificity for each condition were measured over a range of different contrasts and sizes of inhomogeneity for the two scaling techniques. The new method was found to preserve sensitivity in all cases while the traditional technique resulted in significant degradation of sensitivity in certain cases.

Bas-relief generation using adaptive histogram equalization.

PubMed

Sun, Xianfang; Rosin, Paul L; Martin, Ralph R; Langbein, Frank C

2009-01-01

An algorithm is presented to automatically generate bas-reliefs based on adaptive histogram equalization (AHE), starting from an input height field. A mesh model may alternatively be provided, in which case a height field is first created via orthogonal or perspective projection. The height field is regularly gridded and treated as an image, enabling a modified AHE method to be used to generate a bas-relief with a user-chosen height range. We modify the original image-contrast-enhancement AHE method to use gradient weights also to enhance the shape features of the bas-relief. To effectively compress the height field, we limit the height-dependent scaling factors used to compute relative height variations in the output from height variations in the input; this prevents any height differences from having too great effect. Results of AHE over different neighborhood sizes are averaged to preserve information at different scales in the resulting bas-relief. Compared to previous approaches, the proposed algorithm is simple and yet largely preserves original shape features. Experiments show that our results are, in general, comparable to and in some cases better than the best previously published methods.

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

Nonlinear histogram binning for quantitative analysis of lung tissue fibrosis in high-resolution CT data

NASA Astrophysics Data System (ADS)

Zavaletta, Vanessa A.; Bartholmai, Brian J.; Robb, Richard A.

2007-03-01

Diffuse lung diseases, such as idiopathic pulmonary fibrosis (IPF), can be characterized and quantified by analysis of volumetric high resolution CT scans of the lungs. These data sets typically have dimensions of 512 x 512 x 400. It is too subjective and labor intensive for a radiologist to analyze each slice and quantify regional abnormalities manually. Thus, computer aided techniques are necessary, particularly texture analysis techniques which classify various lung tissue types. Second and higher order statistics which relate the spatial variation of the intensity values are good discriminatory features for various textures. The intensity values in lung CT scans range between [-1024, 1024]. Calculation of second order statistics on this range is too computationally intensive so the data is typically binned between 16 or 32 gray levels. There are more effective ways of binning the gray level range to improve classification. An optimal and very efficient way to nonlinearly bin the histogram is to use a dynamic programming algorithm. The objective of this paper is to show that nonlinear binning using dynamic programming is computationally efficient and improves the discriminatory power of the second and higher order statistics for more accurate quantification of diffuse lung disease.

SPAM- SPECTRAL ANALYSIS MANAGER (DEC VAX/VMS VERSION)

NASA Technical Reports Server (NTRS)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

SPAM- SPECTRAL ANALYSIS MANAGER (UNIX VERSION)

NASA Technical Reports Server (NTRS)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

Use of TRMM Rainfall Information in Improving Long-Term, Satellite-Based Global Precipitation Analyses

NASA Technical Reports Server (NTRS)

Starr, David OC. (Technical Monitor); Adler, Robert F.; Huffman, George; Curtis, Scott; Bolvin, David; Nelkin, Eric

2002-01-01

The TRMM rainfall products are inter-compared among themselves and to the 23 year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/ GEWEX) Global Precipitation Climatology Project (GPCP). Ways in which the TRMM-based estimates can be used to improve the long-term data set are described. These include improvement of the passive microwave algorithm that is applied to the 15 year SSM/I record and calibration or adjustment of the current GPCP fields utilizing the 4-5 year overlap of TRMM and GPCP. A comparison of the GPCP monthly surface precipitation fields and the TRMM-based multi-satellite analyses indicates that the two are similar, but have significant differences that relate to the different input data sets. Although on a zonal average basis over the ocean the two analyses are similar in the deep Tropics, there are subtle differences between the eastern and western Pacific Ocean in the relative magnitudes. In mid-latitudes the GPCP has somewhat larger mean precipitation than TRMM. Statistical comparisons of TRMM and GPCP monthly fields are carried out in terms of histogram matching for both ocean and land regions and for small areas to diagnose differences. These comparisons form the basis for a TRMM calibration of the GPCP fields using matched histograms over regional areas as a function of season. Although final application of this procedure will likely await the Version 6 of the TRMM products, tests using Version 5 are shown that provide a TRMM-calibrated GPCP version that will produce an improved climatology and a more accurate month-to-month precipitation analysis for the last 20 years.

Contrasting the co-variability of daytime cloud and precipitation over tropical land and ocean

NASA Astrophysics Data System (ADS)

Jin, Daeho; Oreopoulos, Lazaros; Lee, Dongmin; Cho, Nayeong; Tan, Jackson

2018-03-01

The co-variability of cloud and precipitation in the extended tropics (35° N-35° S) is investigated using contemporaneous data sets for a 13-year period. The goal is to quantify potential relationships between cloud type fractions and precipitation events of particular strength. Particular attention is paid to whether the relationships exhibit different characteristics over tropical land and ocean. A primary analysis metric is the correlation coefficient between fractions of individual cloud types and frequencies within precipitation histogram bins that have been matched in time and space. The cloud type fractions are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) joint histograms of cloud top pressure and cloud optical thickness in 1° grid cells, and the precipitation frequencies come from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) data set aggregated to the same grid.

It is found that the strongest coupling (positive correlation) between clouds and precipitation occurs over ocean for cumulonimbus clouds and the heaviest rainfall. While the same cloud type and rainfall bin are also best correlated over land compared to other combinations, the correlation magnitude is weaker than over ocean. The difference is attributed to the greater size of convective systems over ocean. It is also found that both over ocean and land the anti-correlation of strong precipitation with weak (i.e., thin and/or low) cloud types is of greater absolute strength than positive correlations between weak cloud types and weak precipitation. Cloud type co-occurrence relationships explain some of the cloud-precipitation anti-correlations. Weak correlations between weaker rainfall and clouds indicate poor predictability for precipitation when cloud types are known, and this is even more true over land than over ocean.

[The heterogeneity of blood flow on magnetic resonance imaging: a biomarker for grading cerebral astrocytomas].

PubMed

Revert Ventura, A J; Sanz Requena, R; Martí-Bonmatí, L; Pallardó, Y; Jornet, J; Gaspar, C

2014-01-01

To study whether the histograms of quantitative parameters of perfusion in MRI obtained from tumor volume and peritumor volume make it possible to grade astrocytomas in vivo. We included 61 patients with histological diagnoses of grade II, III, or IV astrocytomas who underwent T2*-weighted perfusion MRI after intravenous contrast agent injection. We manually selected the tumor volume and peritumor volume and quantified the following perfusion parameters on a voxel-by-voxel basis: blood volume (BV), blood flow (BF), mean transit time (TTM), transfer constant (K(trans)), washout coefficient, interstitial volume, and vascular volume. For each volume, we obtained the corresponding histogram with its mean, standard deviation, and kurtosis (using the standard deviation and kurtosis as measures of heterogeneity) and we compared the differences in each parameter between different grades of tumor. We also calculated the mean and standard deviation of the highest 10% of values. Finally, we performed a multiparametric discriminant analysis to improve the classification. For tumor volume, we found statistically significant differences among the three grades of tumor for the means and standard deviations of BV, BF, and K(trans), both for the entire distribution and for the highest 10% of values. For the peritumor volume, we found no significant differences for any parameters. The discriminant analysis improved the classification slightly. The quantification of the volume parameters of the entire region of the tumor with BV, BF, and K(trans) is useful for grading astrocytomas. The heterogeneity represented by the standard deviation of BF is the most reliable diagnostic parameter for distinguishing between low grade and high grade lesions. Copyright © 2011 SERAM. Published by Elsevier Espana. All rights reserved.

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.

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.

Self organising maps for visualising and modelling

PubMed Central

2012-01-01

The paper describes the motivation of SOMs (Self Organising Maps) and how they are generally more accessible due to the wider available modern, more powerful, cost-effective computers. Their advantages compared to Principal Components Analysis and Partial Least Squares are discussed. These allow application to non-linear data, are not so dependent on least squares solutions, normality of errors and less influenced by outliers. In addition there are a wide variety of intuitive methods for visualisation that allow full use of the map space. Modern problems in analytical chemistry include applications to cultural heritage studies, environmental, metabolomic and biological problems result in complex datasets. Methods for visualising maps are described including best matching units, hit histograms, unified distance matrices and component planes. Supervised SOMs for classification including multifactor data and variable selection are discussed as is their use in Quality Control. The paper is illustrated using four case studies, namely the Near Infrared of food, the thermal analysis of polymers, metabolomic analysis of saliva using NMR, and on-line HPLC for pharmaceutical process monitoring. PMID:22594434

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)

Performance Evaluation of EnKF-based Hydrogeological Site Characterization using Color Coherent Vectors

NASA Astrophysics Data System (ADS)

Moslehi, M.; de Barros, F.

2017-12-01

Complexity of hydrogeological systems arises from the multi-scale heterogeneity and insufficient measurements of their underlying parameters such as hydraulic conductivity and porosity. An inadequate characterization of hydrogeological properties can significantly decrease the trustworthiness of numerical models that predict groundwater flow and solute transport. Therefore, a variety of data assimilation methods have been proposed in order to estimate hydrogeological parameters from spatially scarce data by incorporating the governing physical models. In this work, we propose a novel framework for evaluating the performance of these estimation methods. We focus on the Ensemble Kalman Filter (EnKF) approach that is a widely used data assimilation technique. It reconciles multiple sources of measurements to sequentially estimate model parameters such as the hydraulic conductivity. Several methods have been used in the literature to quantify the accuracy of the estimations obtained by EnKF, including Rank Histograms, RMSE and Ensemble Spread. However, these commonly used methods do not regard the spatial information and variability of geological formations. This can cause hydraulic conductivity fields with very different spatial structures to have similar histograms or RMSE. We propose a vision-based approach that can quantify the accuracy of estimations by considering the spatial structure embedded in the estimated fields. Our new approach consists of adapting a new metric, Color Coherent Vectors (CCV), to evaluate the accuracy of estimated fields achieved by EnKF. CCV is a histogram-based technique for comparing images that incorporate spatial information. We represent estimated fields as digital three-channel images and use CCV to compare and quantify the accuracy of estimations. The sensitivity of CCV to spatial information makes it a suitable metric for assessing the performance of spatial data assimilation techniques. Under various factors of data assimilation methods such as number, layout, and type of measurements, we compare the performance of CCV with other metrics such as RMSE. By simulating hydrogeological processes using estimated and true fields, we observe that CCV outperforms other existing evaluation metrics.

Whole brain myelin mapping using T1- and T2-weighted MR imaging data

PubMed Central

Ganzetti, Marco; Wenderoth, Nicole; Mantini, Dante

2014-01-01

Despite recent advancements in MR imaging, non-invasive mapping of myelin in the brain still remains an open issue. Here we attempted to provide a potential solution. Specifically, we developed a processing workflow based on T1-w and T2-w MR data to generate an optimized myelin enhanced contrast image. The workflow allows whole brain mapping using the T1-w/T2-w technique, which was originally introduced as a non-invasive method for assessing cortical myelin content. The hallmark of our approach is a retrospective calibration algorithm, applied to bias-corrected T1-w and T2-w images, that relies on image intensities outside the brain. This permits standardizing the intensity histogram of the ratio image, thereby allowing for across-subject statistical analyses. Quantitative comparisons of image histograms within and across different datasets confirmed the effectiveness of our normalization procedure. Not only did the calibrated T1-w/T2-w images exhibit a comparable intensity range, but also the shape of the intensity histograms was largely corresponding. We also assessed the reliability and specificity of the ratio image compared to other MR-based techniques, such as magnetization transfer ratio (MTR), fractional anisotropy (FA), and fluid-attenuated inversion recovery (FLAIR). With respect to these other techniques, T1-w/T2-w had consistently high values, as well as low inter-subject variability, in brain structures where myelin is most abundant. Overall, our results suggested that the T1-w/T2-w technique may be a valid tool supporting the non-invasive mapping of myelin in the brain. Therefore, it might find important applications in the study of brain development, aging and disease. PMID:25228871

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.

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

Data analysis for GOPEX image frames

NASA Technical Reports Server (NTRS)

Levine, B. M.; Shaik, K. S.; Yan, T.-Y.

1993-01-01

The data analysis based on the image frames received at the Solid State Imaging (SSI) camera of the Galileo Optical Experiment (GOPEX) demonstration conducted between 9-16 Dec. 1992 is described. Laser uplink was successfully established between the ground and the Galileo spacecraft during its second Earth-gravity-assist phase in December 1992. SSI camera frames were acquired which contained images of detected laser pulses transmitted from the Table Mountain Facility (TMF), Wrightwood, California, and the Starfire Optical Range (SOR), Albuquerque, New Mexico. Laser pulse data were processed using standard image-processing techniques at the Multimission Image Processing Laboratory (MIPL) for preliminary pulse identification and to produce public release images. Subsequent image analysis corrected for background noise to measure received pulse intensities. Data were plotted to obtain histograms on a daily basis and were then compared with theoretical results derived from applicable weak-turbulence and strong-turbulence considerations. Processing steps are described and the theories are compared with the experimental results. Quantitative agreement was found in both turbulence regimes, and better agreement would have been found, given more received laser pulses. Future experiments should consider methods to reliably measure low-intensity pulses, and through experimental planning to geometrically locate pulse positions with greater certainty.

Novel Image Encryption Scheme Based on Chebyshev Polynomial and Duffing Map

PubMed Central

2014-01-01

We present a novel image encryption algorithm using Chebyshev polynomial based on permutation and substitution and Duffing map based on substitution. Comprehensive security analysis has been performed on the designed scheme using key space analysis, visual testing, histogram analysis, information entropy calculation, correlation coefficient analysis, differential analysis, key sensitivity test, and speed test. The study demonstrates that the proposed image encryption algorithm shows advantages of more than 10113 key space and desirable level of security based on the good statistical results and theoretical arguments. PMID:25143970

A visual tracking method based on deep learning without online model updating

NASA Astrophysics Data System (ADS)

Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

2018-02-01

The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

Violence detection based on histogram of optical flow orientation

NASA Astrophysics Data System (ADS)

Yang, Zhijie; Zhang, Tao; Yang, Jie; Wu, Qiang; Bai, Li; Yao, Lixiu

2013-12-01

In this paper, we propose a novel approach for violence detection and localization in a public scene. Currently, violence detection is considerably under-researched compared with the common action recognition. Although existing methods can detect the presence of violence in a video, they cannot precisely locate the regions in the scene where violence is happening. This paper will tackle the challenge and propose a novel method to locate the violence location in the scene, which is important for public surveillance. The Gaussian Mixed Model is extended into the optical flow domain in order to detect candidate violence regions. In each region, a new descriptor, Histogram of Optical Flow Orientation (HOFO), is proposed to measure the spatial-temporal features. A linear SVM is trained based on the descriptor. The performance of the method is demonstrated on the publicly available data sets, BEHAVE and CAVIAR.

Statistical Analysis of the Random Telegraph Noise in a 1.1 μm Pixel, 8.3 MP CMOS Image Sensor Using On-Chip Time Constant Extraction Method.

PubMed

Chao, Calvin Yi-Ping; Tu, Honyih; Wu, Thomas Meng-Hsiu; Chou, Kuo-Yu; Yeh, Shang-Fu; Yin, Chin; Lee, Chih-Lin

2017-11-23

A study of the random telegraph noise (RTN) of a 1.1 μm pitch, 8.3 Mpixel CMOS image sensor (CIS) fabricated in a 45 nm backside-illumination (BSI) technology is presented in this paper. A noise decomposition scheme is used to pinpoint the noise source. The long tail of the random noise (RN) distribution is directly linked to the RTN from the pixel source follower (SF). The full 8.3 Mpixels are classified into four categories according to the observed RTN histogram peaks. A theoretical formula describing the RTN as a function of the time difference between the two phases of the correlated double sampling (CDS) is derived and validated by measured data. An on-chip time constant extraction method is developed and applied to the RTN analysis. The effects of readout circuit bandwidth on the settling ratios of the RTN histograms are investigated and successfully accounted for in a simulation using a RTN behavior model.

Highly sensitive image-derived indices of water-stressed plants using hyperspectral imaging in SWIR and histogram analysis

PubMed Central

Kim, David M.; Zhang, Hairong; Zhou, Haiying; Du, Tommy; Wu, Qian; Mockler, Todd C.; Berezin, Mikhail Y.

2015-01-01

The optical signature of leaves is an important monitoring and predictive parameter for a variety of biotic and abiotic stresses, including drought. Such signatures derived from spectroscopic measurements provide vegetation indices – a quantitative method for assessing plant health. However, the commonly used metrics suffer from low sensitivity. Relatively small changes in water content in moderately stressed plants demand high-contrast imaging to distinguish affected plants. We present a new approach in deriving sensitive indices using hyperspectral imaging in a short-wave infrared range from 800 nm to 1600 nm. Our method, based on high spectral resolution (1.56 nm) instrumentation and image processing algorithms (quantitative histogram analysis), enables us to distinguish a moderate water stress equivalent of 20% relative water content (RWC). The identified image-derived indices 15XX nm/14XX nm (i.e. 1529 nm/1416 nm) were superior to common vegetation indices, such as WBI, MSI, and NDWI, with significantly better sensitivity, enabling early diagnostics of plant health. PMID:26531782

PCDAQ, A Windows Based DAQ System

NASA Astrophysics Data System (ADS)

Hogan, Gary

1998-10-01

PCDAQ is a Windows NT based general DAQ/Analysis/Monte Carlo shell developed as part of the Proton Radiography project at LANL (Los Alamos National Laboratory). It has been adopted by experiments outside of the Proton Radiography project at Brookhaven National Laboratory (BNL) and at LANL. The program provides DAQ, Monte Carlo, and replay (disk file input) modes. Data can be read from hardware (CAMAC) or other programs (ActiveX servers). Future versions will read VME. User supplied data analysis routines can be written in Fortran, C++, or Visual Basic. Histogramming, testing, and plotting packages are provided. Histogram data can be exported to spreadsheets or analyzed in user supplied programs. Plots can be copied and pasted as bitmap objects into other Windows programs or printed. A text database keyed by the run number is provided. Extensive software control flags are provided so that the user can control the flow of data through the program. Control flags can be set either in script command files or interactively. The program can be remotely controlled and data accessed over the Internet through its ActiveX DCOM interface.

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.

Uniform enhancement of optical micro-angiography images using Rayleigh contrast-limited adaptive histogram equalization

PubMed Central

Yousefi, Siavash; Qin, Jia; Zhi, Zhongwei

2013-01-01

Optical microangiography is an imaging technology that is capable of providing detailed functional blood flow maps within microcirculatory tissue beds in vivo. Some practical issues however exist when displaying and quantifying the microcirculation that perfuses the scanned tissue volume. These issues include: (I) Probing light is subject to specular reflection when it shines onto sample. The unevenness of the tissue surface makes the light energy entering the tissue not uniform over the entire scanned tissue volume. (II) The biological tissue is heterogeneous in nature, meaning the scattering and absorption properties of tissue would attenuate the probe beam. These physical limitations can result in local contrast degradation and non-uniform micro-angiogram images. In this paper, we propose a post-processing method that uses Rayleigh contrast-limited adaptive histogram equalization to increase the contrast and improve the overall appearance and uniformity of optical micro-angiograms without saturating the vessel intensity and changing the physical meaning of the micro-angiograms. The qualitative and quantitative performance of the proposed method is compared with those of common histogram equalization and contrast enhancement methods. We demonstrate that the proposed method outperforms other existing approaches. The proposed method is not limited to optical microangiography and can be used in other image modalities such as photo-acoustic tomography and scanning laser confocal microscopy. PMID:23482880

Statistical distribution of wind speeds and directions globally observed by NSCAT

NASA Astrophysics Data System (ADS)

Ebuchi, Naoto

1999-05-01

In order to validate wind vectors derived from the NASA scatterometer (NSCAT), statistical distributions of wind speeds and directions over the global oceans are investigated by comparing with European Centre for Medium-Range Weather Forecasts (ECMWF) wind data. Histograms of wind speeds and directions are calculated from the preliminary and reprocessed NSCAT data products for a period of 8 weeks. For wind speed of the preliminary data products, excessive low wind distribution is pointed out through comparison with ECMWF winds. A hump at the lower wind speed side of the peak in the wind speed histogram is discernible. The shape of the hump varies with incidence angle. Incompleteness of the prelaunch geophysical model function, SASS 2, tentatively used to retrieve wind vectors of the preliminary data products, is considered to cause the skew of the wind speed distribution. On the contrary, histograms of wind speeds of the reprocessed data products show consistent features over the whole range of incidence angles. Frequency distribution of wind directions relative to spacecraft flight direction is calculated to assess self-consistency of the wind directions. It is found that wind vectors of the preliminary data products exhibit systematic directional preference relative to antenna beams. This artificial directivity is also considered to be caused by imperfections in the geophysical model function. The directional distributions of the reprocessed wind vectors show less directivity and consistent features, except for very low wind cases.

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

Using color histograms and SPA-LDA to classify bacteria.

PubMed

de Almeida, Valber Elias; da Costa, Gean Bezerra; de Sousa Fernandes, David Douglas; Gonçalves Dias Diniz, Paulo Henrique; Brandão, Deysiane; de Medeiros, Ana Claudia Dantas; Véras, Germano

2014-09-01

In this work, a new approach is proposed to verify the differentiating characteristics of five bacteria (Escherichia coli, Enterococcus faecalis, Streptococcus salivarius, Streptococcus oralis, and Staphylococcus aureus) by using digital images obtained with a simple webcam and variable selection by the Successive Projections Algorithm associated with Linear Discriminant Analysis (SPA-LDA). In this sense, color histograms in the red-green-blue (RGB), hue-saturation-value (HSV), and grayscale channels and their combinations were used as input data, and statistically evaluated by using different multivariate classifiers (Soft Independent Modeling by Class Analogy (SIMCA), Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA), Partial Least Squares Discriminant Analysis (PLS-DA) and Successive Projections Algorithm-Linear Discriminant Analysis (SPA-LDA)). The bacteria strains were cultivated in a nutritive blood agar base layer for 24 h by following the Brazilian Pharmacopoeia, maintaining the status of cell growth and the nature of nutrient solutions under the same conditions. The best result in classification was obtained by using RGB and SPA-LDA, which reached 94 and 100 % of classification accuracy in the training and test sets, respectively. This result is extremely positive from the viewpoint of routine clinical analyses, because it avoids bacterial identification based on phenotypic identification of the causative organism using Gram staining, culture, and biochemical proofs. Therefore, the proposed method presents inherent advantages, promoting a simpler, faster, and low-cost alternative for bacterial identification.

[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).

Methods in quantitative image analysis.

PubMed

Oberholzer, M; Ostreicher, M; Christen, H; Brühlmann, M

1996-05-01

The main steps of image analysis are image capturing, image storage (compression), correcting imaging defects (e.g. non-uniform illumination, electronic-noise, glare effect), image enhancement, segmentation of objects in the image and image measurements. Digitisation is made by a camera. The most modern types include a frame-grabber, converting the analog-to-digital signal into digital (numerical) information. The numerical information consists of the grey values describing the brightness of every point within the image, named a pixel. The information is stored in bits. Eight bits are summarised in one byte. Therefore, grey values can have a value between 0 and 256 (2(8)). The human eye seems to be quite content with a display of 5-bit images (corresponding to 64 different grey values). In a digitised image, the pixel grey values can vary within regions that are uniform in the original scene: the image is noisy. The noise is mainly manifested in the background of the image. For an optimal discrimination between different objects or features in an image, uniformity of illumination in the whole image is required. These defects can be minimised by shading correction [subtraction of a background (white) image from the original image, pixel per pixel, or division of the original image by the background image]. The brightness of an image represented by its grey values can be analysed for every single pixel or for a group of pixels. The most frequently used pixel-based image descriptors are optical density, integrated optical density, the histogram of the grey values, mean grey value and entropy. The distribution of the grey values existing within an image is one of the most important characteristics of the image. However, the histogram gives no information about the texture of the image. The simplest way to improve the contrast of an image is to expand the brightness scale by spreading the histogram out to the full available range. Rules for transforming the grey value histogram of an existing image (input image) into a new grey value histogram (output image) are most quickly handled by a look-up table (LUT). The histogram of an image can be influenced by gain, offset and gamma of the camera. Gain defines the voltage range, offset defines the reference voltage and gamma the slope of the regression line between the light intensity and the voltage of the camera. A very important descriptor of neighbourhood relations in an image is the co-occurrence matrix. The distance between the pixels (original pixel and its neighbouring pixel) can influence the various parameters calculated from the co-occurrence matrix. The main goals of image enhancement are elimination of surface roughness in an image (smoothing), correction of defects (e.g. noise), extraction of edges, identification of points, strengthening texture elements and improving contrast. In enhancement, two types of operations can be distinguished: pixel-based (point operations) and neighbourhood-based (matrix operations). The most important pixel-based operations are linear stretching of grey values, application of pre-stored LUTs and histogram equalisation. The neighbourhood-based operations work with so-called filters. These are organising elements with an original or initial point in their centre. Filters can be used to accentuate or to suppress specific structures within the image. Filters can work either in the spatial or in the frequency domain. The method used for analysing alterations of grey value intensities in the frequency domain is the Hartley transform. Filter operations in the spatial domain can be based on averaging or ranking the grey values occurring in the organising element. The most important filters, which are usually applied, are the Gaussian filter and the Laplace filter (both averaging filters), and the median filter, the top hat filter and the range operator (all ranking filters). Segmentation of objects is traditionally based on threshold grey values. (AB

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis.

PubMed

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine; Peet, Andrew

2018-05-02

Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians' skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. ©Niloufar Zarinabad, Emma M Meeus, Karen Manias, Katharine Foster, Andrew Peet. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 02.05.2018.

In Vivo Imaging of Tau Pathology Using Magnetic Resonance Imaging Textural Analysis

PubMed Central

Colgan, Niall; Ganeshan, Balaji; Harrison, Ian F.; Ismail, Ozama; Holmes, Holly E.; Wells, Jack A.; Powell, Nick M.; O'Callaghan, James M.; O'Neill, Michael J.; Murray, Tracey K.; Ahmed, Zeshan; Collins, Emily C.; Johnson, Ross A.; Groves, Ashley; Lythgoe, Mark F.

2017-01-01

Background: Non-invasive characterization of the pathological features of Alzheimer's disease (AD) could enhance patient management and the development of therapeutic strategies. Magnetic resonance imaging texture analysis (MRTA) has been used previously to extract texture descriptors from structural clinical scans in AD to determine cerebral tissue heterogeneity. In this study, we examined the potential of MRTA to specifically identify tau pathology in an AD mouse model and compared the MRTA metrics to histological measures of tau burden. Methods: MRTA was applied to T2 weighted high-resolution MR images of nine 8.5-month-old rTg4510 tau pathology (TG) mice and 16 litter matched wild-type (WT) mice. MRTA comprised of the filtration-histogram technique, where the filtration step extracted and enhanced features of different sizes (fine, medium, and coarse texture scales), followed by quantification of texture using histogram analysis (mean gray level intensity, mean intensity, entropy, uniformity, skewness, standard-deviation, and kurtosis). MRTA was applied to manually segmented regions of interest (ROI) drawn within the cortex, hippocampus, and thalamus regions and the level of tau burden was assessed in equivalent regions using histology. Results: Texture parameters were markedly different between WT and TG in the cortex (E, p < 0.01, K, p < 0.01), the hippocampus (K, p < 0.05) and in the thalamus (K, p < 0.01). In addition, we observed significant correlations between histological measurements of tau burden and kurtosis in the cortex, hippocampus and thalamus. Conclusions: MRTA successfully differentiated WT and TG in brain regions with varying degrees of tau pathology (cortex, hippocampus, and thalamus) based on T2 weighted MR images. Furthermore, the kurtosis measurement correlated with histological measures of tau burden. This initial study indicates that MRTA may have a role in the early diagnosis of AD and the assessment of tau pathology using routinely acquired structural MR images. PMID:29163005

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.

Feature and contrast enhancement of mammographic image based on multiscale analysis and morphology.

PubMed

Wu, Shibin; Yu, Shaode; Yang, Yuhan; Xie, Yaoqin

2013-01-01

A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII).

Feature and Contrast Enhancement of Mammographic Image Based on Multiscale Analysis and Morphology

PubMed Central

Wu, Shibin; Xie, Yaoqin

2013-01-01

A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII). PMID:24416072

A new phase correction method in NMR imaging based on autocorrelation and histogram analysis.

PubMed

Ahn, C B; Cho, Z H

1987-01-01

A new statistical approach to phase correction in NMR imaging is proposed. The proposed scheme consists of first-and zero-order phase corrections each by the inverse multiplication of estimated phase error. The first-order error is estimated by the phase of autocorrelation calculated from the complex valued phase distorted image while the zero-order correction factor is extracted from the histogram of phase distribution of the first-order corrected image. Since all the correction procedures are performed on the spatial domain after completion of data acquisition, no prior adjustments or additional measurements are required. The algorithm can be applicable to most of the phase-involved NMR imaging techniques including inversion recovery imaging, quadrature modulated imaging, spectroscopic imaging, and flow imaging, etc. Some experimental results with inversion recovery imaging as well as quadrature spectroscopic imaging are shown to demonstrate the usefulness of the algorithm.

Monitoring Short-term Cosmic-ray Spectral Variations Using Neutron Monitor Time-delay Measurements

NASA Astrophysics Data System (ADS)

Ruffolo, D.; Sáiz, A.; Mangeard, P.-S.; Kamyan, N.; Muangha, P.; Nutaro, T.; Sumran, S.; Chaiwattana, C.; Gasiprong, N.; Channok, C.; Wuttiya, C.; Rujiwarodom, M.; Tooprakai, P.; Asavapibhop, B.; Bieber, J. W.; Clem, J.; Evenson, P.; Munakata, K.

2016-01-01

Neutron monitors (NMs) are ground-based detectors of cosmic-ray showers that are widely used for high-precision monitoring of changes in the Galactic cosmic-ray (GCR) flux due to solar storms and solar wind variations. In the present work, we show that a single neutron monitor station can also monitor short-term changes in the GCR spectrum, avoiding the systematic uncertainties in comparing data from different stations, by means of NM time-delay histograms. Using data for 2007-2014 from the Princess Sirindhorn Neutron Monitor, a station at Doi Inthanon, Thailand, with the world’s highest vertical geomagnetic cutoff rigidity of 16.8 GV, we have developed an analysis of time-delay histograms that removes the chance coincidences that can dominate conventional measures of multiplicity. We infer the “leader fraction” L of neutron counts that do not follow a previous neutron count in the same counter from the same atmospheric secondary, which is inversely related to the actual multiplicity and increases for increasing GCR spectral index. After correction for atmospheric pressure and water vapor, we find that L indicates substantial short-term GCR spectral hardening during some but not all Forbush decreases in GCR flux due to solar storms. Such spectral data from Doi Inthanon provide information about cosmic-ray energies beyond the Earth’s maximum geomagnetic cutoff, extending the reach of the worldwide NM network and opening a new avenue in the study of short-term GCR decreases.

Effects of voxelization on dose volume histogram accuracy

NASA Astrophysics Data System (ADS)

Sunderland, Kyle; Pinter, Csaba; Lasso, Andras; Fichtinger, Gabor

2016-03-01

PURPOSE: In radiotherapy treatment planning systems, structures of interest such as targets and organs at risk are stored as 2D contours on evenly spaced planes. In order to be used in various algorithms, contours must be converted into binary labelmap volumes using voxelization. The voxelization process results in lost information, which has little effect on the volume of large structures, but has significant impact on small structures, which contain few voxels. Volume differences for segmented structures affects metrics such as dose volume histograms (DVH), which are used for treatment planning. Our goal is to evaluate the impact of voxelization on segmented structures, as well as how factors like voxel size affects metrics, such as DVH. METHODS: We create a series of implicit functions, which represent simulated structures. These structures are sampled at varying resolutions, and compared to labelmaps with high sub-millimeter resolutions. We generate DVH and evaluate voxelization error for the same structures at different resolutions by calculating the agreement acceptance percentage between the DVH. RESULTS: We implemented tools for analysis as modules in the SlicerRT toolkit based on the 3D Slicer platform. We found that there were large DVH variation from the baseline for small structures or for structures located in regions with a high dose gradient, potentially leading to the creation of suboptimal treatment plans. CONCLUSION: This work demonstrates that labelmap and dose volume voxel size is an important factor in DVH accuracy, which must be accounted for in order to ensure the development of accurate treatment plans.

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.

Using Anisotropic 3D Minkowski Functionals for Trabecular Bone Characterization and Biomechanical Strength Prediction in Proximal Femur Specimens

PubMed Central

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

2017-01-01

The ability of Anisotropic Minkowski Functionals (AMFs) to capture local anisotropy while evaluating topological properties of the underlying gray-level structures has been previously demonstrated. We evaluate the ability of this approach to characterize local structure properties of trabecular bone micro-architecture in ex vivo proximal femur specimens, as visualized on multi-detector CT, for purposes of biomechanical bone strength prediction. To this end, volumetric AMFs were computed locally for each voxel of volumes of interest (VOI) extracted from the femoral head of 146 specimens. The local anisotropy captured by such AMFs was quantified using a fractional anisotropy measure; the magnitude and direction of anisotropy at every pixel was stored in histograms that served as a feature vectors that characterized the VOIs. A linear multi-regression analysis algorithm was used to predict the failure load (FL) from the feature sets; the predicted FL was compared to the true FL determined through biomechanical testing. The prediction performance was measured by the root mean square error (RMSE) for each feature set. The best prediction performance was obtained from the fractional anisotropy histogram of AMF Euler Characteristic (RMSE = 1.01 ± 0.13), which was significantly better than MDCT-derived mean BMD (RMSE = 1.12 ± 0.16, p<0.05). We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding regional trabecular bone quality and contribute to improved bone strength prediction, which is important for improving the clinical assessment of osteoporotic fracture risk. PMID:29170581

MONITORING SHORT-TERM COSMIC-RAY SPECTRAL VARIATIONS USING NEUTRON MONITOR TIME-DELAY MEASUREMENTS

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

Ruffolo, D.; Sáiz, A.; Mangeard, P.-S.

Neutron monitors (NMs) are ground-based detectors of cosmic-ray showers that are widely used for high-precision monitoring of changes in the Galactic cosmic-ray (GCR) flux due to solar storms and solar wind variations. In the present work, we show that a single neutron monitor station can also monitor short-term changes in the GCR spectrum, avoiding the systematic uncertainties in comparing data from different stations, by means of NM time-delay histograms. Using data for 2007–2014 from the Princess Sirindhorn Neutron Monitor, a station at Doi Inthanon, Thailand, with the world’s highest vertical geomagnetic cutoff rigidity of 16.8 GV, we have developed anmore » analysis of time-delay histograms that removes the chance coincidences that can dominate conventional measures of multiplicity. We infer the “leader fraction” L of neutron counts that do not follow a previous neutron count in the same counter from the same atmospheric secondary, which is inversely related to the actual multiplicity and increases for increasing GCR spectral index. After correction for atmospheric pressure and water vapor, we find that L indicates substantial short-term GCR spectral hardening during some but not all Forbush decreases in GCR flux due to solar storms. Such spectral data from Doi Inthanon provide information about cosmic-ray energies beyond the Earth’s maximum geomagnetic cutoff, extending the reach of the worldwide NM network and opening a new avenue in the study of short-term GCR decreases.« less

Texture operator for snow particle classification into snowflake and graupel

NASA Astrophysics Data System (ADS)

Nurzyńska, Karolina; Kubo, Mamoru; Muramoto, Ken-ichiro

2012-11-01

In order to improve the estimation of precipitation, the coefficients of Z-R relation should be determined for each snow type. Therefore, it is necessary to identify the type of falling snow. Consequently, this research addresses a problem of snow particle classification into snowflake and graupel in an automatic manner (as these types are the most common in the study region). Having correctly classified precipitation events, it is believed that it will be possible to estimate the related parameters accurately. The automatic classification system presented here describes the images with texture operators. Some of them are well-known from the literature: first order features, co-occurrence matrix, grey-tone difference matrix, run length matrix, and local binary pattern, but also a novel approach to design simple local statistic operators is introduced. In this work the following texture operators are defined: mean histogram, min-max histogram, and mean-variance histogram. Moreover, building a feature vector, which is based on the structure created in many from mentioned algorithms is also suggested. For classification, the k-nearest neighbourhood classifier was applied. The results showed that it is possible to achieve correct classification accuracy above 80% by most of the techniques. The best result of 86.06%, was achieved for operator built from a structure achieved in the middle stage of the co-occurrence matrix calculation. Next, it was noticed that describing an image with two texture operators does not improve the classification results considerably. In the best case the correct classification efficiency was 87.89% for a pair of texture operators created from local binary pattern and structure build in a middle stage of grey-tone difference matrix calculation. This also suggests that the information gathered by each texture operator is redundant. Therefore, the principal component analysis was applied in order to remove the unnecessary information and additionally reduce the length of the feature vectors. The improvement of the correct classification efficiency for up to 100% is possible for methods: min-max histogram, texture operator built from structure achieved in a middle stage of co-occurrence matrix calculation, texture operator built from a structure achieved in a middle stage of grey-tone difference matrix creation, and texture operator based on a histogram, when the feature vector stores 99% of initial information.

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

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.

Design of microcontroller-based EMG and the analysis of EMG signals.

PubMed

Güler, Nihal Fatma; Hardalaç, Firat

2002-04-01

In this work, a microcontroller-based EMG designed and tested on 40 patients. When the patients are in rest, the fast Fourier transform (FFT) analysis was applied to EMG signals recorded from right leg peroneal region. The histograms are constructed from the results of the FFT analysis. The analysis results shows that the amplitude of fibrillation potential of the muscle fiber of 30 patients measured from peroneal region is low and the duration is short. This is the reason why the motor nerves degenerated and 10 patients were found to be healthy.

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.

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.

A novel pre-processing technique for improving image quality in digital breast tomosynthesis.

PubMed

Kim, Hyeongseok; Lee, Taewon; Hong, Joonpyo; Sabir, Sohail; Lee, Jung-Ryun; Choi, Young Wook; Kim, Hak Hee; Chae, Eun Young; Cho, Seungryong

2017-02-01

Nonlinear pre-reconstruction processing of the projection data in computed tomography (CT) where accurate recovery of the CT numbers is important for diagnosis is usually discouraged, for such a processing would violate the physics of image formation in CT. However, one can devise a pre-processing step to enhance detectability of lesions in digital breast tomosynthesis (DBT) where accurate recovery of the CT numbers is fundamentally impossible due to the incompleteness of the scanned data. Since the detection of lesions such as micro-calcifications and mass in breasts is the purpose of using DBT, it is justified that a technique producing higher detectability of lesions is a virtue. A histogram modification technique was developed in the projection data domain. Histogram of raw projection data was first divided into two parts: One for the breast projection data and the other for background. Background pixel values were set to a single value that represents the boundary between breast and background. After that, both histogram parts were shifted by an appropriate amount of offset and the histogram-modified projection data were log-transformed. Filtered-backprojection (FBP) algorithm was used for image reconstruction of DBT. To evaluate performance of the proposed method, we computed the detectability index for the reconstructed images from clinically acquired data. Typical breast border enhancement artifacts were greatly suppressed and the detectability of calcifications and masses was increased by use of the proposed method. Compared to a global threshold-based post-reconstruction processing technique, the proposed method produced images of higher contrast without invoking additional image artifacts. In this work, we report a novel pre-processing technique that improves detectability of lesions in DBT and has potential advantages over the global threshold-based post-reconstruction processing technique. The proposed method not only increased the lesion detectability but also reduced typical image artifacts pronounced in conventional FBP-based DBT. © 2016 American Association of Physicists in Medicine.

SU-F-I-45: An Automated Technique to Measure Image Contrast in Clinical CT Images

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

Sanders, J; Abadi, E; Meng, B

Purpose: To develop and validate an automated technique for measuring image contrast in chest computed tomography (CT) exams. Methods: An automated computer algorithm was developed to measure the distribution of Hounsfield units (HUs) inside four major organs: the lungs, liver, aorta, and bones. These organs were first segmented or identified using computer vision and image processing techniques. Regions of interest (ROIs) were automatically placed inside the lungs, liver, and aorta and histograms of the HUs inside the ROIs were constructed. The mean and standard deviation of each histogram were computed for each CT dataset. Comparison of the mean and standardmore » deviation of the HUs in the different organs provides different contrast values. The ROI for the bones is simply the segmentation mask of the bones. Since the histogram for bones does not follow a Gaussian distribution, the 25th and 75th percentile were computed instead of the mean. The sensitivity and accuracy of the algorithm was investigated by comparing the automated measurements with manual measurements. Fifteen contrast enhanced and fifteen non-contrast enhanced chest CT clinical datasets were examined in the validation procedure. Results: The algorithm successfully measured the histograms of the four organs in both contrast and non-contrast enhanced chest CT exams. The automated measurements were in agreement with manual measurements. The algorithm has sufficient sensitivity as indicated by the near unity slope of the automated versus manual measurement plots. Furthermore, the algorithm has sufficient accuracy as indicated by the high coefficient of determination, R2, values ranging from 0.879 to 0.998. Conclusion: Patient-specific image contrast can be measured from clinical datasets. The algorithm can be run on both contrast enhanced and non-enhanced clinical datasets. The method can be applied to automatically assess the contrast characteristics of clinical chest CT images and quantify dependencies that may not be captured in phantom data.« less

The method of selection of leukocytes in images of preparations of peripheral blood and bone marrow

NASA Astrophysics Data System (ADS)

Zakharenko, Y. V.; Nikitaev, V. G.; Polyakov, E. V.; Seldyukov, S. O.

2017-01-01

Study of the segmentation method on the basis of histogram analysis for the selection of leukocytes in the images of blood and bone marrow in the diagnosis of acute leukemia was conducted in this paper. Method of filtering was offered to eliminate the artifacts, resulting from the selection of leukocytes.

CHOBS: Color Histogram of Block Statistics for Automatic Bleeding Detection in Wireless Capsule Endoscopy Video

PubMed Central

Ghosh, Tonmoy; Wahid, Khan A.

2018-01-01

Wireless capsule endoscopy (WCE) is the most advanced technology to visualize whole gastrointestinal (GI) tract in a non-invasive way. But the major disadvantage here, it takes long reviewing time, which is very laborious as continuous manual intervention is necessary. In order to reduce the burden of the clinician, in this paper, an automatic bleeding detection method for WCE video is proposed based on the color histogram of block statistics, namely CHOBS. A single pixel in WCE image may be distorted due to the capsule motion in the GI tract. Instead of considering individual pixel values, a block surrounding to that individual pixel is chosen for extracting local statistical features. By combining local block features of three different color planes of RGB color space, an index value is defined. A color histogram, which is extracted from those index values, provides distinguishable color texture feature. A feature reduction technique utilizing color histogram pattern and principal component analysis is proposed, which can drastically reduce the feature dimension. For bleeding zone detection, blocks are classified using extracted local features that do not incorporate any computational burden for feature extraction. From extensive experimentation on several WCE videos and 2300 images, which are collected from a publicly available database, a very satisfactory bleeding frame and zone detection performance is achieved in comparison to that obtained by some of the existing methods. In the case of bleeding frame detection, the accuracy, sensitivity, and specificity obtained from proposed method are 97.85%, 99.47%, and 99.15%, respectively, and in the case of bleeding zone detection, 95.75% of precision is achieved. The proposed method offers not only low feature dimension but also highly satisfactory bleeding detection performance, which even can effectively detect bleeding frame and zone in a continuous WCE video data. PMID:29468094

Illusory Late Heavy Bombardments

NASA Astrophysics Data System (ADS)

Boehnke, P.; Harrison, M.

2016-12-01

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 and a significant portion of the evidence now marshaled for its existence comes from histograms of 40Ar/39Ar "plateau" ages. Despite the lack of erosion and plate tectonics, the lunar crust does not retain a perfect impact record due to protracted crust formation, lunar volcanism, and overprinting from subsequent impact events. Indeed, virtually all Apollo-era samples show 40Ar/39Ar age spectrum disturbances due to later re-heating events. This provides evidence that partial 40Ar resetting is a significant feature of lunar 40Ar/39Ar analyses which could bias interpretation of bombardment histories due to "plateau" ages being misleadingly young. In order to examine the effects of partial resetting on the inference of bombardment histories from "plateau" ages, we combine chronologic information derived from the early heating steps of each 40Ar/39Ar analysis, as this represents a good approximation of the timing of the last reheating event, with a first-order physical model of 40Ar* diffusion in Apollo samples. We use this modeling framework and data compilation to examine the uniqueness of inverting "plateau" age histograms from synthetic impact histories. Our results show that "plateau" histograms tend to yield age peaks, even in those cases where the input impact history did not contain such a spike. That is, monotonically declining impact histories yield apparent episodes that could be misinterpreted as LHB-type events. Since H-chondrites and HED meteorites also show apparent impact spikes, we extend our conclusions to impact histories for meteorite parent bodies as well. We conclude that the assignment of apparent "plateau" ages bears an undesirably high degree of subjectivity. When compounded by inappropriately simplistic interpretations of histograms constructed from such "plateau" ages, impact spikes that are more apparent than real can emerge.

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.

Measurement and statistical analysis of single-molecule current-voltage characteristics, transition voltage spectroscopy, and tunneling barrier height.

PubMed

Guo, Shaoyin; Hihath, Joshua; Díez-Pérez, Ismael; Tao, Nongjian

2011-11-30

We report on the measurement and statistical study of thousands of current-voltage characteristics and transition voltage spectra (TVS) of single-molecule junctions with different contact geometries that are rapidly acquired using a new break junction method at room temperature. This capability allows one to obtain current-voltage, conductance voltage, and transition voltage histograms, thus adding a new dimension to the previous conductance histogram analysis at a fixed low-bias voltage for single molecules. This method confirms the low-bias conductance values of alkanedithiols and biphenyldithiol reported in literature. However, at high biases the current shows large nonlinearity and asymmetry, and TVS allows for the determination of a critically important parameter, the tunneling barrier height or energy level alignment between the molecule and the electrodes of single-molecule junctions. The energy level alignment is found to depend on the molecule and also on the contact geometry, revealing the role of contact geometry in both the contact resistance and energy level alignment of a molecular junction. Detailed statistical analysis further reveals that, despite the dependence of the energy level alignment on contact geometry, the variation in single-molecule conductance is primarily due to contact resistance rather than variations in the energy level alignment.

HFE (Human Factors Engineering) Technology for Navy Weapon System Acquisition.

DTIC Science & Technology

1979-07-01

requirements 2-31 to electrical components using: Failure Modes and Effects Analysis ( FMEA ) and LOR data, component design requirements and a selected...3- 60 * ,.- .- I; L , , _ m m _ --- : " I. I ._ . - I- The use of SAINT can specify various outputs of the simulation, histograms, plots, summary...Electro Safety . 60 .98 .95 .65 .92 .70 .42 .62 Personnel Relationships .74 .70 .79 .63 .40 .77 .85 .80 Electro Circuit Analysis .63 .90 .95 .58 .40

Using gamma index to flag changes in anatomy during image-guided radiation therapy of head and neck cancer.

PubMed

Schaly, Bryan; Kempe, Jeff; Venkatesan, Varagur; Mitchell, Sylvia; Battista, Jerry J

2017-11-01

During radiation therapy of head and neck cancer, the decision to consider replanning a treatment because of anatomical changes has significant resource implications. We developed an algorithm that compares cone-beam computed tomography (CBCT) image pairs and provides an automatic alert as to when remedial action may be required. Retrospective CBCT data from ten head and neck cancer patients that were replanned during their treatment was used to train the algorithm on when to recommend a repeat CT simulation (re-CT). An additional 20 patients (replanned and not replanned) were used to validate the predictive power of the algorithm. CBCT images were compared in 3D using the gamma index, combining Hounsfield Unit (HU) difference with distance-to-agreement (DTA), where the CBCT study acquired on the first fraction is used as the reference. We defined the match quality parameter (MQP x ) as a difference between the x th percentiles of the failed-pixel histograms calculated from the reference gamma comparison and subsequent comparisons, where the reference gamma comparison is taken from the first two CBCT images acquired during treatment. The decision to consider re-CT was based on three consecutive MQP values being less than or equal to a threshold value, such that re-CT recommendations were within ±3 fractions of the actual re-CT order date for the training cases. Receiver-operator characteristic analysis showed that the best trade-off in sensitivity and specificity was achieved using gamma criteria of 3 mm DTA and 30 HU difference, and the 80 th percentile of the failed-pixel histogram. A sensitivity of 82% and 100% was achieved in the training and validation cases, respectively, with a false positive rate of ~30%. We have demonstrated that gamma analysis of CBCT-acquired anatomy can be used to flag patients for possible replanning in a manner consistent with local clinical practice guidelines. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Clarification to "Examining Rater Errors in the Assessment of Written Composition with a Many-Faceted Rasch Model."

ERIC Educational Resources Information Center

Englehard, George, Jr.

1996-01-01

Data presented in figure three of the article cited may be misleading in that the automatic scaling procedure used by the computer program that generated the histogram highlighted spikes that would look different with different histogram methods. (SLD)

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)

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

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.

Pedestrian detection from thermal images: A sparse representation based approach

NASA Astrophysics Data System (ADS)

Qi, Bin; John, Vijay; Liu, Zheng; Mita, Seiichi

2016-05-01

Pedestrian detection, a key technology in computer vision, plays a paramount role in the applications of advanced driver assistant systems (ADASs) and autonomous vehicles. The objective of pedestrian detection is to identify and locate people in a dynamic environment so that accidents can be avoided. With significant variations introduced by illumination, occlusion, articulated pose, and complex background, pedestrian detection is a challenging task for visual perception. Different from visible images, thermal images are captured and presented with intensity maps based objects' emissivity, and thus have an enhanced spectral range to make human beings perceptible from the cool background. In this study, a sparse representation based approach is proposed for pedestrian detection from thermal images. We first adopted the histogram of sparse code to represent image features and then detect pedestrian with the extracted features in an unimodal and a multimodal framework respectively. In the unimodal framework, two types of dictionaries, i.e. joint dictionary and individual dictionary, are built by learning from prepared training samples. In the multimodal framework, a weighted fusion scheme is proposed to further highlight the contributions from features with higher separability. To validate the proposed approach, experiments were conducted to compare with three widely used features: Haar wavelets (HWs), histogram of oriented gradients (HOG), and histogram of phase congruency (HPC) as well as two classification methods, i.e. AdaBoost and support vector machine (SVM). Experimental results on a publicly available data set demonstrate the superiority of the proposed approach.

Knowledge-based low-level image analysis for computer vision systems

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.; Baxi, Himanshu; Ranganath, M. V.

1988-01-01

Two algorithms for entry-level image analysis and preliminary segmentation are proposed which are flexible enough to incorporate local properties of the image. The first algorithm involves pyramid-based multiresolution processing and a strategy to define and use interlevel and intralevel link strengths. The second algorithm, which is designed for selected window processing, extracts regions adaptively using local histograms. The preliminary segmentation and a set of features are employed as the input to an efficient rule-based low-level analysis system, resulting in suboptimal meaningful segmentation.

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…

Comparative analysis of feature extraction methods in satellite imagery

NASA Astrophysics Data System (ADS)

Karim, Shahid; Zhang, Ye; Asif, Muhammad Rizwan; Ali, Saad

2017-10-01

Feature extraction techniques are extensively being used in satellite imagery and getting impressive attention for remote sensing applications. The state-of-the-art feature extraction methods are appropriate according to the categories and structures of the objects to be detected. Based on distinctive computations of each feature extraction method, different types of images are selected to evaluate the performance of the methods, such as binary robust invariant scalable keypoints (BRISK), scale-invariant feature transform, speeded-up robust features (SURF), features from accelerated segment test (FAST), histogram of oriented gradients, and local binary patterns. Total computational time is calculated to evaluate the speed of each feature extraction method. The extracted features are counted under shadow regions and preprocessed shadow regions to compare the functioning of each method. We have studied the combination of SURF with FAST and BRISK individually and found very promising results with an increased number of features and less computational time. Finally, feature matching is conferred for all methods.

Environmental Justice Assessment for Transportation

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

Mills, G.S.; Neuhauser, K.S.

1999-04-05

Application of Executive Order 12898 to risk assessment of highway or rail transport of hazardous materials has proven difficult; the location and conditions affecting the propagation of a plume of hazardous material released in a potential accident are unknown, in general. Therefore, analyses have only been possible in geographically broad or approximate manner. The advent of geographic information systems and development of software enhancements at Sandia National Laboratories have made kilometer-by-kilometer analysis of populations tallied by U.S. Census Blocks along entire routes practicable. Tabulations of total, or racially/ethnically distinct, populations close to a route, its alternatives, or the broader surroundingmore » area, can then be compared and differences evaluated statistically. This paper presents methods of comparing populations and their racial/ethnic compositions using simple tabulations, histograms and Chi Squared tests for statistical significance of differences found. Two examples of these methods are presented: comparison of two routes and comparison of a route with its surroundings.« less

Improving material identification by combining x-ray and neutron tomography

NASA Astrophysics Data System (ADS)

LaManna, Jacob M.; Hussey, Daniel S.; Baltic, Eli; Jacobson, David L.

2017-09-01

X-rays and neutrons provide complementary non-destructive probes for the analysis of structure and chemical composition of materials. Contrast differences between the modes arise due to the differences in interaction with matter. Due to the high sensitivity to hydrogen, neutrons excel at separating liquid water or hydrogenous phases from the underlying structure while X-rays resolve the solid structure. Many samples of interest, such as fluid flow in porous materials or curing concrete, are stochastic or slowly changing with time which makes analysis of sequential imaging with X-rays and neutrons difficult as the sample may change between scans. To alleviate this issue, NIST has developed a system for simultaneous X-ray and neutron tomography by orienting a 90 keVpeak micro-focus X-ray tube orthogonally to a thermal neutron beam. This system allows for non-destructive, multimodal tomography of dynamic or stochastic samples while penetrating through sample environment equipment such as pressure and flow vessels. Current efforts are underway to develop methods for 2D histogram based segmentation of reconstructed volumes. By leveraging the contrast differences between X-rays and neutrons, greater histogram peak separation can occur in 2D vs 1D enabling improved material identification.

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.

Redshift data and statistical inference

NASA Technical Reports Server (NTRS)

Newman, William I.; Haynes, Martha P.; Terzian, Yervant

1994-01-01

Frequency histograms and the 'power spectrum analysis' (PSA) method, the latter developed by Yu & Peebles (1969), have been widely employed as techniques for establishing the existence of periodicities. We provide a formal analysis of these two classes of methods, including controlled numerical experiments, to better understand their proper use and application. In particular, we note that typical published applications of frequency histograms commonly employ far greater numbers of class intervals or bins than is advisable by statistical theory sometimes giving rise to the appearance of spurious patterns. The PSA method generates a sequence of random numbers from observational data which, it is claimed, is exponentially distributed with unit mean and variance, essentially independent of the distribution of the original data. We show that the derived random processes is nonstationary and produces a small but systematic bias in the usual estimate of the mean and variance. Although the derived variable may be reasonably described by an exponential distribution, the tail of the distribution is far removed from that of an exponential, thereby rendering statistical inference and confidence testing based on the tail of the distribution completely unreliable. Finally, we examine a number of astronomical examples wherein these methods have been used giving rise to widespread acceptance of statistically unconfirmed conclusions.

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.

Comparison of conventional and digital radiography for radiometric differentiation of dental cements.

PubMed

Baksi, B Güniz; Ermis, R Banu

2007-10-01

To test the efficacy of conventional radiometry with indirect digital image analysis in the assessment of the relative radiopacity of dental cements used as liners or bases compared to human enamel and dentin. Disks of 15 different dental cements, 5 mm in diameter and 2 mm thick, were exposed to radiation together with 2-mm-thick disks of enamel and dentin and an aluminum step wedge. Density was evaluated by digital transmission densitometry and with the histogram function of an image analysis program following digitization of the radiographs with a flatbed scanner. A higher number of dental cements were discriminated from both dentin and enamel with conventional radiographic densitometer. All the cements examined, except Ionoseal (Voco) and Ionobond (Voco), were more radiopaque than dentin. With both methods, Chelon-Silver (3M ESPE) had the highest radiopacity and glass-ionomer cements the lowest. Radiodensity of dental cements can be differentiated with a high probability with the conventional radiometric method.

How to resolve microsecond current fluctuations in single ion channels: The power of beta distributions

PubMed Central

Schroeder, Indra

2015-01-01

Abstract A main ingredient for the understanding of structure/function correlates of ion channels is the quantitative description of single-channel gating and conductance. However, a wealth of information provided from fast current fluctuations beyond the temporal resolution of the recording system is often ignored, even though it is close to the time window accessible to molecular dynamics simulations. This kind of current fluctuations provide a special technical challenge, because individual opening/closing or blocking/unblocking events cannot be resolved, and the resulting averaging over undetected events decreases the single-channel current. Here, I briefly summarize the history of fast-current fluctuation analysis and focus on the so-called “beta distributions.” This tool exploits characteristics of current fluctuation-induced excess noise on the current amplitude histograms to reconstruct the true single-channel current and kinetic parameters. A guideline for the analysis and recent applications demonstrate that a construction of theoretical beta distributions by Markov Model simulations offers maximum flexibility as compared to analytical solutions. PMID:26368656

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

User Guide for the Plotting Software for the Los Alamos National Laboratory Nuclear Weapons Analysis Tools Version 2.0

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

Cleland, Timothy James

The Los Alamos National Laboratory Plotting Software for the Nuclear Weapons Analysis Tools is a Java™ application based upon the open source library JFreeChart. The software provides a capability for plotting data on graphs with a rich variety of display options while allowing the viewer interaction via graph manipulation and scaling to best view the data. The graph types include XY plots, Date XY plots, Bar plots and Histogram plots.

Investigation of 3D histograms of oriented gradients for image-based registration of CT with interventional CBCT

NASA Astrophysics Data System (ADS)

Trimborn, Barbara; Wolf, Ivo; Abu-Sammour, Denis; Henzler, Thomas; Schad, Lothar R.; Zöllner, Frank G.

2017-03-01

Image registration of preprocedural contrast-enhanced CTs to intraprocedual cone-beam computed tomography (CBCT) can provide additional information for interventional liver oncology procedures such as transcatheter arterial chemoembolisation (TACE). In this paper, a novel similarity metric for gradient-based image registration is proposed. The metric relies on the patch-based computation of histograms of oriented gradients (HOG) building the basis for a feature descriptor. The metric was implemented in a framework for rigid 3D-3D-registration of pre-interventional CT with intra-interventional CBCT data obtained during the workflow of a TACE. To evaluate the performance of the new metric, the capture range was estimated based on the calculation of the mean target registration error and compared to the results obtained with a normalized cross correlation metric. The results show that 3D HOG feature descriptors are suitable as image-similarity metric and that the novel metric can compete with established methods in terms of registration accuracy

Extended census transform histogram for land-use scene classification

NASA Astrophysics Data System (ADS)

Yuan, Baohua; Li, Shijin

2017-04-01

With the popular use of high-resolution satellite images, more and more research efforts have been focused on land-use scene classification. In scene classification, effective visual features can significantly boost the final performance. As a typical texture descriptor, the census transform histogram (CENTRIST) has emerged as a very powerful tool due to its effective representation ability. However, the most prominent limitation of CENTRIST is its small spatial support area, which may not necessarily be adept at capturing the key texture characteristics. We propose an extended CENTRIST (eCENTRIST), which is made up of three subschemes in a greater neighborhood scale. The proposed eCENTRIST not only inherits the advantages of CENTRIST but also encodes the more useful information of local structures. Meanwhile, multichannel eCENTRIST, which can capture the interactions from multichannel images, is developed to obtain higher categorization accuracy rates. Experimental results demonstrate that the proposed method can achieve competitive performance when compared to state-of-the-art methods.

Segmentation by fusion of histogram-based k-means clusters in different color spaces.

PubMed

Mignotte, Max

2008-05-01

This paper presents a new, simple, and efficient segmentation approach, based on a fusion procedure which aims at combining several segmentation maps associated to simpler partition models in order to finally get a more reliable and accurate segmentation result. The different label fields to be fused in our application are given by the same and simple (K-means based) clustering technique on an input image expressed in different color spaces. Our fusion strategy aims at combining these segmentation maps with a final clustering procedure using as input features, the local histogram of the class labels, previously estimated and associated to each site and for all these initial partitions. This fusion framework remains simple to implement, fast, general enough to be applied to various computer vision applications (e.g., motion detection and segmentation), and has been successfully applied on the Berkeley image database. The experiments herein reported in this paper illustrate the potential of this approach compared to the state-of-the-art segmentation methods recently proposed in the literature.

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.

Fractal-Based Image Analysis In Radiological Applications

NASA Astrophysics Data System (ADS)

Dellepiane, S.; Serpico, S. B.; Vernazza, G.; Viviani, R.

1987-10-01

We present some preliminary results of a study aimed to assess the actual effectiveness of fractal theory and to define its limitations in the area of medical image analysis for texture description, in particular, in radiological applications. A general analysis to select appropriate parameters (mask size, tolerance on fractal dimension estimation, etc.) has been performed on synthetically generated images of known fractal dimensions. Moreover, we analyzed some radiological images of human organs in which pathological areas can be observed. Input images were subdivided into blocks of 6x6 pixels; then, for each block, the fractal dimension was computed in order to create fractal images whose intensity was related to the D value, i.e., texture behaviour. Results revealed that the fractal images could point out the differences between normal and pathological tissues. By applying histogram-splitting segmentation to the fractal images, pathological areas were isolated. Two different techniques (i.e., the method developed by Pentland and the "blanket" method) were employed to obtain fractal dimension values, and the results were compared; in both cases, the appropriateness of the fractal description of the original images was verified.