scholarly journals Statistical Assessment of Discrimination Capabilities of a Fractional Calculus Based Image Watermarking System for Gaussian Watermarks

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 255
Author(s):  
Mario Gonzalez-Lee ◽  
Hector Vazquez-Leal ◽  
Luis J. Morales-Mendoza ◽  
Mariko Nakano-Miyatake ◽  
Hector Perez-Meana ◽  
...  

In this paper, we explore the advantages of a fractional calculus based watermarking system for detecting Gaussian watermarks. To reach this goal, we selected a typical watermarking scheme and replaced the detection equation set by another set of equations derived from fractional calculus principles; then, we carried out a statistical assessment of the performance of both schemes by analyzing the Receiver Operating Characteristic (ROC) curve and the False Positive Percentage (FPP) when they are used to detect Gaussian watermarks. The results show that the ROC of a fractional equation based scheme has 48.3% more Area Under the Curve (AUC) and a False Positives Percentage median of 0.2% whilst the selected typical watermarking scheme has 3%. In addition, the experimental results suggest that the target applications of fractional schemes for detecting Gaussian watermarks are as a semi-fragile image watermarking systems robust to Gaussian noise.

2019 ◽  
Vol 110 (7-8) ◽  
pp. 697-704
Author(s):  
Yiming Liu ◽  
Wenchuan Chen ◽  
Wei Cui ◽  
Haikuan Liu ◽  
Xiangfei Zhou ◽  
...  

Purpose: To assess whether parameters on preprocedural CT can be utilized to predict the response of NETLM to transcatheter arterial bland embolization (TAE). Methods: We retrospectively reviewed 135 target lesions from 48 NETLM patients who underwent TAE and with complete preprocedural multiphasic CT. Parameters on preprocedural CT including the longest diameter, mean attenuation value in nonenhanced, arterial, and portal-venous phases were collected from each target lesion. Radiological responses were assessed according to RECIST 1.1. The parameters of responder lesions and nonresponder lesions were compared. Arterial enhancement index (AEI) and portal-venous enhancement index (PEI) were calculated. The predictive function of AEI and PEI on tumor response was analyzed by receiver operating characteristic (ROC) curve. Results: A total of 72.6% target lesions had a partial response. For patients, the objective response rate was 72.9%. Mean attenuation values of responder lesions were significantly higher than nonresponder lesions in both arterial and portal-venous phases (105.36 ± 37.24 vs. 76.01 ± 19.19, p < 0.001; 96.61 ± 24.04 vs. 82.12 ± 21.37, p = 0.002). ROC curve showed that both AEI and PEI were effective in predicting tumor response (area under the curve [AUC] 0.757, p < 0.001; AUC 0.655, p = 0.005). Conclusion: AEI and PEI, parameters from evaluation of CT pretreatment attenuation of NETLMs, could predict response to TAE treatment.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 1412-1412
Author(s):  
Hayder Saeed ◽  
Ryan Woods ◽  
Joshua Lester ◽  
Gregory Monohan

Abstract Background Ferritin is a ubiquitous protein involved in intracellular iron storage; however, there is growing evidence of its implication in immune suppression, given its overexpression in autoimmune diseases. Secondary Hemophagocytic Lymphohistiocytosis (HLH) typically presents in adults. In the clinical protocol HLH-04, the diagnosis of HLH is made by having either molecular testing representative of HLH or by having five or more of the following eight criteria: 1) fever, 2) splenomegaly, 3) cytopenias (affecting at least 2 cell lineages), 4) hypertriglyceridemia and/or hypofibrinogenemia, 5) hemophagocytosis in bone marrow, spleen, or lymph nodes, 6) diminished NK-cell activity, 7) elevated soluble CD25 (i.e. sIL-2 receptor), and 8) hyperferritinemia. An elevated ferritin level was defined as >500 ng/mL. Ferritin levels in critically ill patients are poorly understood since levels are driven by multiple variables related to comorbidities and ferritin’s role as an acute phase reactant in the setting of an acute illness. Many conditions associated with critically ill patients can mimic HLH clinically, including malignancies (leukemia, lymphoma, and other solid tumors), infections (viral, bacterial, or parasitic), and rheumatoid disorders. Incidentally, these same conditions can lead to secondary HLH, making the discrimination between actual cases of HLH and clinically similar conditions quite difficult at times. We hereby present the first retrospective review of hyperferritinimia in the critically ill adult patient population and its relation to HLH. Methods We performed a retrospective review of patients admitted to our academic medical center intensive care unit (MICU) between 2004 and 2014 with serum ferritin level measured during their hospital stay above 500 ng/mL. We then reviewed their discharge diagnosis (based upon the treating physicians’ diagnosis) to investigate the utility of defining a ferritin level, which would provide adequate specificity while maintaining a reasonable sensitivity in identifying those patients with HLH. Discharge diagnoses were then categorized into major groups such as sepsis/infection, hematological malignancy, HLH, respiratory disease, neurological disease, HIV, transplant complications, renal disease, or cardiac disease; median ferritin levels were calculated for each category. Results We found 343 patients with a serum ferritin level >500 ng/mL who were admitted to the MICU during their hospital stay. Median age of this patient group was 58 years with a range of 20 to 88 years; 209 were men and 136 were women. Caucasians represented 82%. Nine patients carried HLH as their discharge diagnosis, which represented 2.6% of all patients. The most common discharge diagnosis (35%) was sepsis/infection (Figure 1). HLH had the highest ferritin level with a median of 25,652 ng/mL (range 1,977 to 100,727 ng/mL). The closest second ferritin median was in hematological malignancies (7,154 ng/mL; range 561 to 60,774 ng/mL, Figure 2). To obtain optimal sensitivity and specificity of different ferritin values (Table 1) in identifying HLH patients, an ROC curve, with a pretest probability of 50% and cost ratio of 1, showed the optimal ferritin cutoff to be 3,951 ng/mL which, in our population, would have a sensitivity of 88% (95% CI 51-99%) and specificity of 82% (95% CI 78-86%, Figures 3). Conclusion While ferritin is an integral test for the diagnosis of HLH, a value of >500 ng/mL lacks specificity in adults in the critical care setting. Increasing the diagnostic value to 3,900 ng/mL in this patient population improves specificity while maintaining an acceptable sensitivity to aid in the diagnosis of patients with HLH. Figure 1. Diseases by elevated ferritin >500 ng/mL. Figure 1. Diseases by elevated ferritin >500 ng/mL. Figure 2. Ferritin distributions over the major 11 disease categories. Boxes represent the 25-75 percentiles. Dots represent the 5/95 outliers. Figure 2. Ferritin distributions over the major 11 disease categories. Boxes represent the 25-75 percentiles. Dots represent the 5/95 outliers. Table 1. Different proposed cutoffs with their prospective sensitivity, specificity, and likelihood ratios (LR). Cutoff > Sensitivity % 95% CI Specificity % 95% CI LR + LR - 503.50 100.00 66.37% to 100.0% 0.30 0.007557% to 1.652% 1.00 0.00 2514.00 88.89 51.75% to 99.72% 75.22 70.24% to 79.76% 3.59 0.15 5020.00 77.78 39.99% to 97.19% 85.67 81.46% to 89.24% 5.43 0.26 Figure 3. Figure 4. Receiver operating characteristic (ROC) curve for maximum serum ferritin. (A) is Area under the curve. Figure 3. Figure 4. Receiver operating characteristic (ROC) curve for maximum serum ferritin. (A) is Area under the curve. Disclosures No relevant conflicts of interest to declare.


2020 ◽  
Vol 48 (10) ◽  
pp. 030006052096908
Author(s):  
Ting Song ◽  
Lili Wang ◽  
Ruopei Xin ◽  
Liping Zhang ◽  
Yun Tian

Objective This study compared the diagnostic performance of alpha-fetoprotein (AFP) and des-gamma-carboxyprothrombin (DCP) in early-stage hepatitis B virus-related hepatocellular carcinoma (HBV-HCC) under different backgrounds. Methods Patients were enrolled and divided in four groups: chronic HBV infection (CHB), liver cirrhosis (LC), early-stage CHB-HCC, and early-stage LC-HCC. Serum AFP and DCP levels were measured. Receiver-operating characteristic (ROC) curve and area under the curve (AUC) analyses were applied to compare the diagnostic performance of DCP and AFP for HCC. Results In total, 200 patients were enrolled, including 48, 64, 33, and 55 patients with CHB, LC, CHB-HCC, and LC-HCC, respectively. ROC curve analysis revealed that the AUCs of AFP, DCP, and their combination in differentiating early-stage LC-HCC from LC were 0.776, 0.758, and 0.786, respectively. The values of these markers in discriminating early-stage CHB-HCC from CHB were 0.828, 0.731, and 0.862, respectively. Conclusions DCP was inferior to AFP in differentiating early-stage CHB-HCC from CHB. However, AFP and DCP displayed similar performance in distinguishing early-stage LC-HCC and LC.


2020 ◽  
Author(s):  
Juanjuan Chen ◽  
Dongling Tang ◽  
Chu Xu ◽  
Zhili Niu ◽  
Huan Li ◽  
...  

Abstract Objective To evaluate the potential diagnostic value of growth differentiation factor 15 (GDF15) alone and its combination with protein induced by vitamin K absence-II (PIVKA-II) and alpha-fetoprotein (AFP) for hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC). Methods Serum levels of GDF15, PIVKA-II, and AFP were measured in 110 patients with HBV-associated HCC, 70 patients with HBV-related liver cirrhosis (LC), 70 patients with chronic hepatitis B (CHB), and 110 healthy patients. Results Serum GDF15 was positively related to the levels of PIVKA-II and AFP in patients with HCC (r = 0.352 and r = 0.378; all P &lt;.0001). When the receiver operating characteristic (ROC) curve was plotted for patients with HCC vs all control patients, serum GDF15 had diagnostic parameters of an area under the curve (AUC) of 0.693, a sensitivity of 67.30%, and a specificity of 66.70%, which were lower than parameters for PIVKA-II and AFP (all P &lt;.0001). When the ROC curve was plotted for patients with HCC vs patients with LC, the combination of GDF15 and PIVKA-II had the highest diagnostic accuracy of AUC and specificity as compared with other combinations (all P &lt;.0001). Conclusion We found that GDF15 is a potent serum marker for the detection of HBV-associated HCC and that PIVKA-II combined with GDF15 can improve diagnostic accuracy for HBV-associated HCC.


2015 ◽  
Author(s):  
Ειρήνη Τερζή

Μελετήθηκε η συμβολή της άλφα1-μικροσφαιρίνης (alpha1-microglobulin, α1M) - ενός μέλους της οικογένειας των λιποκαλινών, που αποτελεί δείκτη εγγύς νεφροσωληναριακής δυσλειτουργίας - στην πρώιμη διαγνωστική της σχετιζόμενης με την σήψη οξείας νεφρικής βλάβης (acute kidney injury, AKI). Η μελέτη επικεντρώθηκε σε βαρέως πάσχοντες ασθενείς μιας πολυδύναμης Μονάδας Εντατικής Θεραπείας (Μ.Ε.Θ.). Από την προοπτική παρακολούθηση 290 ασθενών που εισήχθησαν για νοσηλεία σε διάστημα ενός έτους, μελετήθηκαν 45 σηπτικοί ασθενείς, εκ των οποίων οι 16 (35.6%) εκδήλωσαν νεφρική ανεπάρκεια. Η α1Μ προσδιορίσθηκε σε δείγματα ούρων από συλλογές ούρων 24ώρου κατά το σηπτικό επεισόδιο και σε συγκεκριμένα χρονικά διαστήματα έκτοτε. Η διαγνωστική ικανότητα του βιοδείκτη εκτιμήθηκε με τον μη παραμετρικό υπολογισμό της περιοχής κάτω από την καμπύλη μίας καμπύλης λειτουργικού χαρακτηριστικού δέκτη (area under the curve (AUC) of the receiver operating characteristic (ROC) curve, AUCROC). Τα επίπεδα της α1Μ ήταν σημαντικά υψηλότερα σε όλους τους σηπτικούς ασθενείς (μέση τιμή επιπέδων σε όλα τα δείγματα στο σηπτικό επεισόδιο 46.02 ± 7.17 mg/l) και παρουσίασαν αυξητική τάση στους ασθενείς που τελικά ανέπτυξαν σηπτική νεφρική ανεπάρκεια. Η AUCROC για την πρόβλεψη της σηπτικής ΑKΙ σύμφωνα με τα επίπεδα της α1M 24 ώρες πριν την εμφάνιση της νεφρικής προσβολής ήταν 0.739 (ευαισθησία 87.5%, ειδικότητα 62.07%, τιμή-όριο 47.9 mg/l). Τα επίπεδα της α1Μ 24 ώρες πριν την σηπτική νεφρική προσβολή, η κρεατινίνη ορού και η βαθμολογία βαρύτητας νόσου κατά APACHE II στο επεισόδιο της σήψης, αναδείχθηκαν ως οι σημαντικότεροι ανεξάρτητοι προγνωστικοί παράγοντες πρόβλεψης της ΑΚΙ. Ο συνδυασμός των ανωτέρω τριών παραμέτρων βελτίωσε την AUCROC της πρόγνωση της AKI σε 0.944. Τα αποτελέσματα υποστηρίζουν την ιδέα πως τα επίπεδα της α1Μ στα ούρα θα μπορούσαν να συμβάλουν στην πρώιμη διάκριση των σηπτικών ασθενών που εξελίσσονται σε ΑΚΙ και μπορεί να αποδειχθούν χρήσιμος βιοδείκτης. Παράλληλα, αναδεικνύουν ως θέμα για περαιτέρω έρευνα την παθογενετική εμπλοκή της α1Μ στην σήψη και στην σηπτική ΑΚΙ.


Neurosurgery ◽  
2020 ◽  
Vol 87 (3) ◽  
pp. 530-537 ◽  
Author(s):  
Robert J Elbin ◽  
Scott L Zuckerman ◽  
Allen K Sills ◽  
Jeff R Crandall ◽  
David J Lessley ◽  
...  

Abstract BACKGROUND On-field visible signs (VS) are used to help identify sport-related concussion (SRC) in the National Football League (NFL). However, the predictive utility of a VS checklist for SRC is unknown. OBJECTIVE To report the frequency, sensitivity, specificity, and predictive value of VS in a cohort of NFL athletes. METHODS On-field VS ratings from 2 experts who independently reviewed video footage of a cohort of 251 injury plays that resulted in an SRC diagnosis (n = 211) and no diagnosis (n = 40) from the 2017 NFL season were examined. The frequency, sensitivity, specificity, and a receiver operating characteristic (ROC) curve with area under the curve (AUC) were calculated for each VS. RESULTS Slow to get up (65.9%) and motor incoordination (28.4%) were the most frequent VS in concussed athletes, and slow to get up (60.0%) was the most common VS among nonconcussed athletes. The most sensitive VS was slow to get up (66%); the most specific signs in concussed NFL athletes were blank/vacant look and impact seizure (both 100%). Approximately 26% of concussed NFL players did not exhibit a VS, and the overall sensitivity and specificity for the VS checklist to detect SRC were 73% and 65%, respectively. The VS checklist demonstrated “poor” ability to discriminate between SRC and non-SRC groups (AUC = 0.66). CONCLUSION In the NFL, the diagnosis of concussion cannot be made from on-field VS alone. The VS checklist is one part of the comprehensive sideline/acute evaluation of concussion, and the diagnosis remains a multimodal clinical decision.


2020 ◽  
Vol 13 (3) ◽  
pp. 1391
Author(s):  
Jakeline Jesus Silva ◽  
Lucas Prado Osco ◽  
Ana Paula Marques Ramos ◽  
Wesley Barbosa Dourado

O mapeamento da vegetação arbórea em áreas urbanas pode ser realizado por classificação semiautomática ou automática de imagens orbitais ou aéreas. Contudo, esse tipo de tarefa tem um custo computacional dependente da resolução espacial da imagem. Neste estudo é proposto uma abordagem de extração semiautomática de vegetação arbórea em imagens de alta resolução espacial a baixo custo computacional. Trabalhamos com ortofotos de 1m de resolução, disponibilizadas por órgãos gestores públicos. A abordagem proposta aplica um filtro de médias em recortes de imagens, com 500x500 pixels cada. Ao todo utilizamos 90 recortes. Testamos o algoritmo nas seguintes configurações: separadamente nas bandas (azul, verde e vermelho), em imagem colorida (RGB) e em imagem em tons de cinza. Validamos sua performance usando a matriz de confusão e a curva do Receiver Operating Characteristic (ROC), considerando 3.695 pontos distribuídos homogeneamente em todos os recortes de imagens. Comparamos, ainda, a performance do algoritmo com uma classificação supervisionado por pixel (máxima verossimilhança). Obtivemos uma acurácia global de 90,18%, um índice kappa de 0,80 e uma velocidade de processamento de aproximadamente 1 minuto e 30 segundos para o algoritmo proposto em um computador convencional. A curva ROC obteve uma Area Under the Curve (AUC) equivalente a 0,91 para o algoritmo, considerando o resultado de todas as bandas, e um valor de 0,79 para a classificação supervisionada por pixel. Concluímos que nossa abordagem é computacionalmente eficiente para separar as áreas cobertas por vegetação de áreas não cobertas em ambiente urbano. Semiautomatic extraction of arboreal vegetation in urban areas using aerial imagery of high spatial resolution A B S T R A C TMapping of tree vegetation in urban areas can be performed by semi-automatic or automatic classification of orbital or aerial images. However, this type of task has a computational cost dependent on the spatial resolution of the image. This study proposes an approach of semi-automatic tree vegetation extraction in high spatial resolution images at a low computational cost. We work with 1m resolution orthophotos, made available by public management agencies. The proposed approach applies a medium filter on image clippings of 500x500 pixels each. In all, we use 90 clippings. We tested the algorithm in the following configurations: separately in the bands (blue, green and red), color image (RGB) and grayscale image. We validated its performance using the Confusion Matrix and Receiver Operating Characteristic (ROC) curve, considering 3,695 points evenly distributed across all clippings. We also compared the performance of the algorithm with a pixel supervised classification (maximum likelihood). We obtained an overall accuracy of 90.18%, a kappa index of 0.80 and a processing speed of approximately 1 minute and 30 seconds for the proposed algorithm in a conventional computer. The ROC curve obtained an Area Under the Curve (AUC) equivalent to 0.91 for the algorithm, considering the result of all bands, and a value of 0.79 for the supervised pixel classification. We conclude that our approach is computationally efficient for separating areas covered by vegetation from areas not covered in an urban environment.Keywords: digital image processing; image classification; urban environmental planning.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Pablo Martínez-Camblor ◽  
Sonia Pérez-Fernández ◽  
Susana Díaz-Coto

Abstract The receiver operating-characteristic (ROC) curve is a well-known graphical tool routinely used for evaluating the discriminatory ability of continuous markers, referring to a binary characteristic. The area under the curve (AUC) has been proposed as a summarized accuracy index. Higher values of the marker are usually associated with higher probabilities of having the characteristic under study. However, there are other situations where both, higher and lower marker scores, are associated with a positive result. The generalized ROC (gROC) curve has been proposed as a proper extension of the ROC curve to fit these situations. Of course, the corresponding area under the gROC curve, gAUC, has also been introduced as a global measure of the classification capacity. In this paper, we study in deep the gAUC properties. The weak convergence of its empirical estimator is provided while deriving an explicit and useful expression for the asymptotic variance. We also obtain the expression for the asymptotic covariance of related gAUCs and propose a non-parametric procedure to compare them. The finite-samples behavior is studied through Monte Carlo simulations under different scenarios, presenting a real-world problem in order to illustrate its practical application. The R code functions implementing the procedures are provided as Supplementary Material.


2012 ◽  
Vol 24 (10) ◽  
pp. 2789-2824 ◽  
Author(s):  
Takashi Takenouchi ◽  
Osamu Komori ◽  
Shinto Eguchi

While most proposed methods for solving classification problems focus on minimization of the classification error rate, we are interested in the receiver operating characteristic (ROC) curve, which provides more information about classification performance than the error rate does. The area under the ROC curve (AUC) is a natural measure for overall assessment of a classifier based on the ROC curve. We discuss a class of concave functions for AUC maximization in which a boosting-type algorithm including RankBoost is considered, and the Bayesian risk consistency and the lower bound of the optimum function are discussed. A procedure derived by maximizing a specific optimum function has high robustness, based on gross error sensitivity. Additionally, we focus on the partial AUC, which is the partial area under the ROC curve. For example, in medical screening, a high true-positive rate to the fixed lower false-positive rate is preferable and thus the partial AUC corresponding to lower false-positive rates is much more important than the remaining AUC. We extend the class of concave optimum functions for partial AUC optimality with the boosting algorithm. We investigated the validity of the proposed method through several experiments with data sets in the UCI repository.


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