Lesion detection in demoscopy images with novel density-based and active contour approaches

<p>Abstract</p> <p>Background</p> <p>Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma and other pigmented skin lesions. Automated assessment tools for dermoscopy images have become an important field of research mainly because of inter- and intra-observer variations in human interpretation. One of the most important steps in dermoscopy image analysis is the detection of lesion borders, since many other features, such as asymmetry, border irregularity, and abrupt border cutoff, rely on the boundary of the lesion. </p> <p>Results</p> <p>To automate the process of delineating the lesions, we employed Active Contour Model (ACM) and boundary-driven density-based clustering (BD-DBSCAN) algorithms on 50 dermoscopy images, which also have ground truths to be used for quantitative comparison. We have observed that ACM and BD-DBSCAN have the same border error of 6.6% on all images. To address noisy images, BD-DBSCAN can perform better delineation than ACM. However, when used with optimum parameters, ACM outperforms BD-DBSCAN, since ACM has a higher recall ratio.</p> <p>Conclusion</p> <p>We successfully proposed two new frameworks to delineate suspicious lesions with i) an ACM integrated approach with sharpening and ii) a fast boundary-driven density-based clustering technique. ACM shrinks a curve toward the boundary of the lesion. To guide the evolution, the model employs the exact solution <abbrgrp><abbr bid="B27">27</abbr></abbrgrp> of a specific form of the Geometric Heat Partial Differential Equation <abbrgrp><abbr bid="B28">28</abbr></abbrgrp>. To make ACM advance through noisy images, an improvement of the model’s boundary condition is under consideration. BD-DBSCAN improves regular density-based algorithm to select query points intelligently.</p

Interpretation, Evaluation and the Semantic Gap ... What if we Were on a Side-Track?

International audienceA significant amount of research in Document Image Analysis, and Machine Perception in general, relies on the extraction and analysis of signal cues with the goal of interpreting them into higher level information. This paper gives an overview on how this interpretation process is usually considered, and how the research communities proceed in evaluating existing approaches and methods developed for realizing these processes. Evaluation being an essential part to measuring the quality of research and assessing the progress of the state-of-the art, our work aims at showing that classical evaluation methods are not necessarily well suited for interpretation problems, or, at least, that they introduce a strong bias, not necessarily visible at first sight, and that new ways of comparing methods and measuring performance are necessary. It also shows that the infamous {\em Semantic Gap} seems to be an inherent and unavoidable part of the general interpretation process, especially when considered within the framework of traditional evaluation. The use of Formal Concept Analysis is put forward to leverage these limitations into a new tool to the analysis and comparison of interpretation contexts

Analysis of density based and fuzzy c-means clustering methods on lesion border extraction in dermoscopy images

<p>Abstract</p> <p>Background</p> <p>Computer-aided segmentation and border detection in dermoscopic images is one of the core components of diagnostic procedures and therapeutic interventions for skin cancer. Automated assessment tools for dermoscopy images have become an important research field mainly because of inter- and intra-observer variations in human interpretation. In this study, we compare two approaches for automatic border detection in dermoscopy images: density based clustering (DBSCAN) and Fuzzy C-Means (FCM) clustering algorithms. In the first approach, if there exists enough density –greater than certain number of points- around a point, then either a new cluster is formed around the point or an existing cluster grows by including the point and its neighbors. In the second approach FCM clustering is used. This approach has the ability to assign one data point into more than one cluster.</p> <p>Results</p> <p>Each approach is examined on a set of 100 dermoscopy images whose manually drawn borders by a dermatologist are used as the ground truth. Error rates; false positives and false negatives along with true positives and true negatives are quantified by comparing results with manually determined borders from a dermatologist. The assessments obtained from both methods are quantitatively analyzed over three accuracy measures: border error, precision, and recall. </p> <p>Conclusion</p> <p>As well as low border error, high precision and recall, visual outcome showed that the DBSCAN effectively delineated targeted lesion, and has bright future; however, the FCM had poor performance especially in border error metric.</p

Burnout Syndrome and alcohol consumption in prison employees

Objective: The aims of this study were to estimate the association between an at-risk drinking pattern and sociodemographic variables, and to compare the mean scores of the factors associated with the Burnout Syndrome, according to the alcohol consumption pattern in staff members from two Brazilian prisons. Methods: A cross-sectional study was developed with 339 participants (response rate = 63.8%). The instruments used were a sociodemographic questionnaire, the Alcohol Use Disorders Identification Test (AUDIT), and the Maslach Burnout Inventory – General Survey (MBI-GS). Results: The participants’ average age was 40.2 (SD = 8.8) years, and 81.0% were male. Among 78.5% of participants (95%CI 74.1 – 82.8) reported consuming alcoholic beverages. The prevalence of at-risk drinking behavior in the sample was 22.4% (95%CI 18.0 – 26.9), and of the Burnout Syndrome was 14.6% (95%CI 10.8 – 18.4). We observed a significant association between at-risk drinking behavior with gender, higher risk for men (OR = 7.32, p < 0.001), smoking, increased risk for smokers (OR = 2.77, p < 0.001), and religious practice, showing lower risks for religion practitioners (OR = 0.364, p < 0.001). We noticed significantly higher mean scores (p < 0.001) of emotional exhaustion and cynicism, and lower scores of professional achievement among individuals who reported consuming alcoholic beverages. Conclusion: Men who smoke were more likely to develop an at-risk drinking pattern, while religion is presented as a protective factor. Individuals who consume alcohol were more affected by the different factors of the Burnout Syndrome

Combination of searches for heavy spin-1 resonances using 139 fb−1 of proton-proton collision data at s = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb−1 of proton-proton collisions at = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, , and tb) or third-generation leptons (τν and ττ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion

Measurement and interpretation of same-sign W boson pair production in association with two jets in pp collisions at s = 13 TeV with the ATLAS detector

This paper presents the measurement of fducial and diferential cross sections for both the inclusive and electroweak production of a same-sign W-boson pair in association with two jets (W±W±jj) using 139 fb−1 of proton-proton collision data recorded at a centre-of-mass energy of √s = 13 TeV by the ATLAS detector at the Large Hadron Collider. The analysis is performed by selecting two same-charge leptons, electron or muon, and at least two jets with large invariant mass and a large rapidity diference. The measured fducial cross sections for electroweak and inclusive W±W±jj production are 2.92 ± 0.22 (stat.) ± 0.19 (syst.)fb and 3.38±0.22 (stat.)±0.19 (syst.)fb, respectively, in agreement with Standard Model predictions. The measurements are used to constrain anomalous quartic gauge couplings by extracting 95% confdence level intervals on dimension-8 operators. A search for doubly charged Higgs bosons H±± that are produced in vector-boson fusion processes and decay into a same-sign W boson pair is performed. The largest deviation from the Standard Model occurs for an H±± mass near 450 GeV, with a global signifcance of 2.5 standard deviations

Search for dark photons in rare Z boson decays with the ATLAS detector

A search for events with a dark photon produced in association with a dark Higgs boson via rare decays of the standard model Z boson is presented, using 139     fb − 1 of √ s = 13     TeV proton-proton collision data recorded by the ATLAS detector at the Large Hadron Collider. The dark boson decays into a pair of dark photons, and at least two of the three dark photons must each decay into a pair of electrons or muons, resulting in at least two same-flavor opposite-charge lepton pairs in the final state. The data are found to be consistent with the background prediction, and upper limits are set on the dark photon’s coupling to the dark Higgs boson times the kinetic mixing between the standard model photon and the dark photon, α D ϵ 2 , in the dark photon mass range of [5, 40] GeV except for the Υ mass window [8.8, 11.1] GeV. This search explores new parameter space not previously excluded by other experiments

Combined measurement of the Higgs boson mass from the H → γγ and H → ZZ∗ → 4ℓ decay channels with the ATLAS detector using √s = 7, 8, and 13 TeV pp collision data

A measurement of the mass of the Higgs boson combining the H → Z Z ∗ → 4 ℓ and H → γ γ decay channels is presented. The result is based on 140     fb − 1 of proton-proton collision data collected by the ATLAS detector during LHC run 2 at a center-of-mass energy of 13 TeV combined with the run 1 ATLAS mass measurement, performed at center-of-mass energies of 7 and 8 TeV, yielding a Higgs boson mass of 125.11 ± 0.09 ( stat ) ± 0.06 ( syst ) = 125.11 ± 0.11     GeV . This corresponds to a 0.09% precision achieved on this fundamental parameter of the Standard Model of particle physics