• Title/Summary/Keyword: Receiver Operating Characteristic

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Image saliency detection based on geodesic-like and boundary contrast maps

  • Guo, Yingchun;Liu, Yi;Ma, Runxin
    • ETRI Journal
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    • v.41 no.6
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    • pp.797-810
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    • 2019
  • Image saliency detection is the basis of perceptual image processing, which is significant to subsequent image processing methods. Most saliency detection methods can detect only a single object with a high-contrast background, but they have no effect on the extraction of a salient object from images with complex low-contrast backgrounds. With the prior knowledge, this paper proposes a method for detecting salient objects by combining the boundary contrast map and the geodesics-like maps. This method can highlight the foreground uniformly and extract the salient objects efficiently in images with low-contrast backgrounds. The classical receiver operating characteristics (ROC) curve, which compares the salient map with the ground truth map, does not reflect the human perception. An ROC curve with distance (distance receiver operating characteristic, DROC) is proposed in this paper, which takes the ROC curve closer to the human subjective perception. Experiments on three benchmark datasets and three low-contrast image datasets, with four evaluation methods including DROC, show that on comparing the eight state-of-the-art approaches, the proposed approach performs well.

Forensic Image Classification using Data Mining Decision Tree (데이터 마이닝 결정나무를 이용한 포렌식 영상의 분류)

  • RHEE, Kang Hyeon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.7
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    • pp.49-55
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    • 2016
  • In digital forensic images, there is a serious problem that is distributed with various image types. For the problem solution, this paper proposes a classification algorithm of the forensic image types. The proposed algorithm extracts the 21-dim. feature vector with the contrast and energy from GLCM (Gray Level Co-occurrence Matrix), and the entropy of each image type. The classification test of the forensic images is performed with an exhaustive combination of the image types. Through the experiments, TP (True Positive) and FN (False Negative) is detected respectively. While it is confirmed that performed class evaluation of the proposed algorithm is rated as 'Excellent(A)' because of the AUROC (Area Under Receiver Operating Characteristic Curve) is 0.9980 by the sensitivity and the 1-specificity. Also, the minimum average decision error is 0.1349. Also, at the minimum average decision error is 0.0179, the whole forensic image types which are involved then, our classification effectiveness is high.

Poor Treatment Outcome of Neuroblastoma and Other Peripheral Nerve Cell Tumors May be Related to Under Usage of Radiotherapy and Socio-Economic Disparity: A US SEER Data Analysis

  • Cheung, Rex
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.9
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    • pp.4587-4592
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    • 2012
  • Purpose: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) neuroblastoma (NB) and other peripheral nerve cell tumors (PNCT) outcome data. This study found under usage of radiotherapy in these patients. Materials and methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for NB and other PNCT. For the risk modeling, each factor was fitted by a generalized linear model to predict the outcome (soft tissue specific death, yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A random sampling algorithm was used to estimate the modeling errors. Risk of neuroendocrine (other endocrine including thymus as coded in SEER) death was computed for the predictors. Results: There were 5261 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 83.8 (97.6) months. The mean (SD) age was 18 (25) years. About 30.45% of patients were un-staged. The SEER staging has high ROC (SD) area of 0.58 (0.01) among the factors tested. We simplified the 4-layered risk levels (local, regional, distant, un-staged/others) to a simpler 3-tiered model with comparable ROC area of 0.59 (0.01). Less than 50% of PNCT patients received radiotherapy (RT) including the ones with localized disease. This avoidance of RT use occurred in adults and children. Conclusion: The high under-staging rate may have precented patients from selecting definitive radiotherapy (RT) after surgery. Using RT for, especially, adult PNCT patients is a potential way to improve outcome.

Optimal Threshold from ROC and CAP Curves (ROC와 CAP 곡선에서의 최적 분류점)

  • Hong, Chong-Sun;Choi, Jin-Soo
    • The Korean Journal of Applied Statistics
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    • v.22 no.5
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    • pp.911-921
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    • 2009
  • Receiver Operating Characteristic(ROC) and Cumulative Accuracy Profile(CAP) curves are two methods used to assess the discriminatory power of different credit-rating approaches. The points of optimal classification accuracy on an ROC curve and of maximal profit on a CAP curve can be found by using iso-performance tangent lines, which are based on the standard notion of accuracy. In this paper, we offer an alternative accuracy measure called the true rate. Using this rate, one can obtain alternative optimal threshold points on both ROC and CAP curves. For most real populations of borrowers, the number of the defaults is much less than that of the non-defaults, and in such cases the true rate may be more efficient than the accuracy rate in terms of cost functions. Moreover, it is shown that both alternative scores of optimal classification accuracy and maximal profit are the identical, and this single score coincides with the score corresponding to Kolmogorov-Smirnov statistic used to test the homogeneous distribution functions of the defaults and non-defaults.

Image Forensic Decision Algorithm using Edge Energy Information of Forgery Image (위·변조 영상의 에지 에너지 정보를 이용한 영상 포렌식 판정 알고리즘)

  • Rhee, Kang Hyeon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.3
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    • pp.75-81
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    • 2014
  • In a distribution of the digital image, there is a serious problem that is distributed an illegal forgery image by pirates. For the problem solution, this paper proposes an image forensic decision algorithm using an edge energy information of forgery image. The algorithm uses SA (Streaking Artifacts) and SPAM (Subtractive Pixel Adjacency Matrix) to extract the edge energy informations of original image according to JPEG compression rate(QF=90, 70, 50 and 30) and the query image. And then it decides the forge whether or not by comparing the edge informations between the original and query image each other. According to each threshold in TCJCR (Threshold by Combination of JPEG Compression Ratios), the matching of the edge informations of original and query image is excused. Through the matching experiments, TP (True Positive) and FN (False Negative) is 87.2% and 13.8% respectively. Thus, the minimum average decision error is 0.1349. Also, it is confirmed that the performed class evaluation of the proposed algorithm is 'Excellent(A)' because of the AUROC (Area Under Receiver Operating Characteristic) curve is 0.9388 by sensitivity and 1-specificity.

Surveying and Optimizing the Predictors for Ependymoma Specific Survival using SEER Data

  • Cheung, Min Rex
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.2
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    • pp.867-870
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    • 2014
  • Purpose: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) ependymoma data to identify predictive models and potential disparity in outcome. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for ependymoma. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict the outcome ('brain and other nervous systems' specific death in yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A random sampling algorithm was used to estimate the modeling errors. Risk of ependymoma death was computed for the predictors for comparison. Results: A total of 3,500 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 79.8 (82.3) months. Some 46% of the patients were female. The mean (S.D.) age was 34.4 (22.8) years. Age was the most predictive factor of outcome. Unknown grade demonstrated a 15% risk of cause specific death compared to 9% for grades I and II, and 36% for grades III and IV. A 5-tiered grade model (with a ROC area 0.48) was optimized to a 3-tiered model (with ROC area of 0.53). This ROC area tied for the second with that for surgery. African-American patients had 21.5% risk of death compared with 16.6% for the others. Some 72.7% of patient who did not get RT had cerebellar or spinal ependymoma. Patients undergoing surgery had 16.3% risk of death, as compared to 23.7% among those who did not have surgery. Conclusion: Grading ependymoma may dramatically improve modeling of data. RT is under used for cerebellum and spinal cord ependymoma and it may be a potential way to improve outcome.

Performance Evaluation of Frame Synchronization Using Pilot Patterns in W-CDMA System (W-CDMA 시스템의 파일럿 패턴을 이용한 프레임 동기 성능 분석)

  • Song Young-Joon;Kim Han-Mook
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.17 no.3 s.106
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    • pp.272-279
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    • 2006
  • In this paper, we evaluate the performance of frame synchronization words of pilot bit patterns which are used for the channel estimation and frame synchronization confirmation in W-CDMA(Wide band Code Division Multiple Access) system. W-CDMA system also uses compressed mode to make measurements from another frequency without a full dual receiver terminal. It is confirmed by using computer simulation that the proposed frame synchronization words also maintain the frame synchronization property in the compressed mode by using the complementary mapping relationship of preferred pair ROC(Receiver Operating Characteristic) curves with probability of detection and false alarm are used to analized the performance of the proposed frame synchronization words by using the various detection metrics such as LLRT(Log Likelyhood Ratio Test), GLRT(Generalied Likelyhood Ratio Test), soft and hard correlation tests in AWGN and Rayleigh fading channels. It is expected that the research results fer the performance of pilot bit patterns of this paper can be useful reference for the design and implementation of frame synchronization in 3rd generation W-CDMA system.

Evaluation of Waist Circumference Cut-off Values as a Marker for Fatty Liver among Japanese Workers

  • Abe, Naomi;Honda, Sumihisa;Jahng, Doosub
    • Safety and Health at Work
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    • v.3 no.4
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    • pp.287-293
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    • 2012
  • Objectives: Metabolic syndrome has received attention as a risk factor for cardiovascular disease, with particular importance attached to visceral fat accumulation, which is associated with lifestyle-related diseases and is strongly correlated with waist circumference. In this study, our aim is to propose waist circumference cut-off values that can be used as a marker for fatty liver based on a sample of workers receiving health checkups in Japan. Methods: This study was conducted in a total of 21,866 workers who underwent periodic health checkups between January 2007 and December 2007. The mean age of the subjects was 47.4 years for men (standard deviation [SD]: 8.0) and 44.7 years for women (SD: 6.9). Evaluation included abdominal ultrasound and measurement of waist circumference, body mass index, fasting blood glucose, triglycerides, high-density lipoprotein cholesterol, and blood pressure. Results: Based on receiver operating characteristic curve analysis, the optimal waist circumference cut-off values were shown as 85.0 cm (sensitivity 0.72, specificity 0.69) for men and 80.0 cm (sensitivity 0.75, specificity 0.78) for women. Conclusion: Abdominal ultrasound is the most efficient means of diagnosing fatty liver, but this examination seldom occurs because the test is not routinely performed at workers' health checkups. In people found to have a high risk of fatty liver, recommendations can be made for abdominal ultrasound based on the waist circumference cut-off values obtained in this study. That is, waist circumference can be used in high risk individuals as an effective marker for early detection of fatty liver.

Comparison of the Diagnostic Validity of Real and Absolute Skin Temperature Differences for Complex Regional Pain Syndrome (복합부위통증증후군 진단 시 좌우 체온 차이의 실제값과 절대값의 진단적 타당도 비교)

  • Nahm, Francis Sahngun;Lee, Pyung Bok;Park, Soo Young;Kim, Yong Chul;Lee, Sang Chul
    • The Korean Journal of Pain
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    • v.22 no.2
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    • pp.146-150
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    • 2009
  • Background: A skin temperature difference is one of the variables used in the diagnosis of complex regional pain syndrome. However, there have been no reports as to whether the real (${\Delta}T$) or absolute value ($|{\Delta}T|$) of skin temperature differences should be used in the diagnosis of complex regional pain syndrome. This study was conducted to compare the diagnostic validity of ${\Delta}T$ with $|{\Delta}T|$ for complex regional pain syndrome using receiver operating characteristic curves (ROC). Methods: Infrared thermographic images were obtained from the 144 patients who were suspected to have CRPS in a unilateral limb. After ${\Delta}T$ and $|{\Delta}T|$ calculation from the thermographic image, ROCs of ${\Delta}T$ and $|{\Delta}T|$ were developed, and the areas under the curve (AUC) for the ROC curves were compared. Results: AUCs of ${\Delta}T$ and $|{\Delta}T|$ were 0.520 and 0.746 respectively, this difference was statistically significant (P < 0.001). Conclusions: Absolute skin temperature difference shows greater validity in the diagnosis of CRPS than ${\Delta}T$. Therefore, $|{\Delta}T|$ is more useful when comparing the skin temperature of CRPS patients.

Prediction model of hypercholesterolemia using body fat mass based on machine learning (머신러닝 기반 체지방 측정정보를 이용한 고콜레스테롤혈증 예측모델)

  • Lee, Bum Ju
    • The Journal of the Convergence on Culture Technology
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    • v.5 no.4
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    • pp.413-420
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    • 2019
  • The purpose of the present study is to develop a model for predicting hypercholesterolemia using an integrated set of body fat mass variables based on machine learning techniques, beyond the study of the association between body fat mass and hypercholesterolemia. For this study, a total of six models were created using two variable subset selection methods and machine learning algorithms based on the Korea National Health and Nutrition Examination Survey (KNHANES) data. Among the various body fat mass variables, we found that trunk fat mass was the best variable for predicting hypercholesterolemia. Furthermore, we obtained the area under the receiver operating characteristic curve value of 0.739 and the Matthews correlation coefficient value of 0.36 in the model using the correlation-based feature subset selection and naive Bayes algorithm. Our findings are expected to be used as important information in the field of disease prediction in large-scale screening and public health research.