Volumetric texture description and discriminant feature selection for MRI

This paper considers the problem of classification of Magnetic Resonance Images using 2D and 3D texture measures. Joint statistics such as co-occurrence matrices are common for analysing texture in 2D since they are simple and effective to implement. However, the computational complexity can be prohibitive especially in 3D. In this work, we develop a texture classification strategy by a sub-band filtering technique that can be extended to 3D. We further propose a feature selection technique based on the Bhattacharyya distance measure that reduces the number of features required for the classification by selecting a set of discriminant features conditioned on a set training texture samples. We describe and illustrate the methodology by quantitatively analysing a series of images: 2D synthetic phantom, 2D natural textures, and MRI of human knees

Source identification for mobile devices, based on wavelet transforms combined with sensor imperfections

One of the most relevant applications of digital image forensics is to accurately identify the device used for taking a given set of images, a problem called source identification. This paper studies recent developments in the field and proposes the mixture of two techniques (Sensor Imperfections and Wavelet Transforms) to get better source identification of images generated with mobile devices. Our results show that Sensor Imperfections and Wavelet Transforms can jointly serve as good forensic features to help trace the source camera of images produced by mobile phones. Furthermore, the model proposed here can also determine with high precision both the brand and model of the device

Association of Over-The-Counter Pharmaceutical Sales with Influenza-Like-Illnesses to Patient Volume in an Urgent Care Setting

We studied the association between OTC pharmaceutical sales and volume of patients with influenza-like-illnesses (ILI) at an urgent care center over one year. OTC pharmaceutical sales explain 36% of the variance in the patient volume, and each standard deviation increase is associated with 4.7 more patient visits to the urgent care center (p<0.0001). Cross-correlation function analysis demonstrated that OTC pharmaceutical sales are significantly associated with patient volume during non-flu season (p<0.0001), but only the sales of cough and cold (p<0.0001) and thermometer (p<0.0001) categories were significant during flu season with a lag of two and one days, respectively. Our study is the first study to demonstrate and measure the relationship between OTC pharmaceutical sales and urgent care center patient volume, and presents strong evidence that OTC sales predict urgent care center patient volume year round. © 2013 Liu et al

QUICKScan: a pragmatic approach to decision support

Decision Support Tools (DST) are a key instrument for preparing legislative proposals and policy initiatives. They provide insight about options, conflicts, synergies and trade-offs between issues, sectors and regions at multiple scales. DST range from integrated systems modelling to value-based knowledge systems resulting from expert groups. The results of the expert groups do not provide regional differentiation making it difficult to obtain useful insights for policy making. The ‘black-box’ complex tools are found not transparent by the decision makers that seek to understand the modelling behind the results to be able to cope with the scientific uncertainty and changing policy context. In addition, the policy questions need to be answered in a short period to fit the time horizon of policy making, e.g. a couple of months, which is possible with expert groups, but the complex models are often not ready to deal with this urgency. The QUICKScan tool aims at filling the gap in the pallet of available tools by defining a methodology -supported by modelling software to visualize quantitative and value-based modelling in the decision process. The tool enables the creation of alternative storylines for policy questions by the stakeholders, and translates these in-situ into a model by combining tacit expert knowledge with available spatial explicit monitoring- and statistical-data. QUICKScan builds on concepts from Participatory Modelling and Participatory GIS and uses visualisation and interpretation tools which are essential to support the exploration of options allowing and facilitating the discussion and interaction on the definition of alternatives, analysing their consequences, determining trade-offs and synergies and compare the consequences of alternatives. The QUICKScan tool is designed to calculate fast, and therefor perform multiple iterations of a modelling exercise during a workshop. The results of each iteration feed the discussion among stakeholders and policy makers creating input for a next iteration

Profiles of US and CT imaging features with a high probability of appendicitis

To identify and evaluate profiles of US and CT features associated with acute appendicitis. Consecutive patients presenting with acute abdominal pain at the emergency department were invited to participate in this study. All patients underwent US and CT. Imaging features known to be associated with appendicitis, and an imaging diagnosis were prospectively recorded by two independent radiologists. A final diagnosis was assigned after 6 months. Associations between appendiceal imaging features and a final diagnosis of appendicitis were evaluated with logistic regression analysis. Appendicitis was assigned to 284 of 942 evaluated patients (30%). All evaluated features were associated with appendicitis. Imaging profiles were created after multivariable logistic regression analysis. Of 147 patients with a thickened appendix, local transducer tenderness and peri-appendiceal fat infiltration on US, 139 (95%) had appendicitis. On CT, 119 patients in whom the appendix was completely visualised, thickened, with peri-appendiceal fat infiltration and appendiceal enhancement, 114 had a final diagnosis of appendicitis (96%). When at least two of these essential features were present on US or CT, sensitivity was 92% (95% CI 89-96%) and 96% (95% CI 93-98%), respectively. Most patients with appendicitis can be categorised within a few imaging profiles on US and CT. When two of the essential features are present the diagnosis of appendicitis can be made accuratel

A comparison of the Accuracy of Ultrasound and Computed Tomography in common diagnoses causing acute abdominal pain

Head-to-head comparison of ultrasound and CT accuracy in common diagnoses causing acute abdominal pain. Consecutive patients with abdominal pain for > 2 h and <5 days referred for imaging underwent both US and CT by different radiologists/radiological residents. An expert panel assigned a final diagnosis. Ultrasound and CT sensitivity and predictive values were calculated for frequent final diagnoses. Effect of patient characteristics and observer experience on ultrasound sensitivity was studied. Frequent final diagnoses in the 1,021 patients (mean age 47; 55% female) were appendicitis (284; 28%), diverticulitis (118; 12%) and cholecystitis (52; 5%). The sensitivity of CT in detecting appendicitis and diverticulitis was significantly higher than that of ultrasound: 94% versus 76% (p <0.01) and 81% versus 61% (p = 0.048), respectively. For cholecystitis, the sensitivity of both was 73% (p = 1.00). Positive predictive values did not differ significantly between ultrasound and CT for these conditions. Ultrasound sensitivity in detecting appendicitis and diverticulitis was not significantly negatively affected by patient characteristics or reader experience. CT misses fewer cases than ultrasound, but both ultrasound and CT can reliably detect common diagnoses causing acute abdominal pain. Ultrasound sensitivity was largely not influenced by patient characteristics and reader experience

Imaging strategies for detection of urgent conditions in patients with acute abdominal pain: diagnostic accuracy study

Objective To identify an optimal imaging strategy for the accurate detection of urgent conditions in patients with acute abdominal pain

Long-term cardiac follow-up of athletes infected with SARS-CoV-2 after resumption of elite-level sports

OBJECTIVE: Longitudinal consequences and potential interactions of COVID-19 and elite-level sports and exercise are unclear. Therefore, we determined the long-term detrimental cardiac effects of the interaction between SARS-CoV-2 infection and the highest level of sports and exercise.METHODS: This prospective controlled study included elite athletes from the Evaluation of Lifetime participation in Intensive Top-level sports and Exercise cohort. Athletes infected with SARS-CoV-2were offered structured, additional cardiovascular screenings, including cardiovascular MRI (CMR). We compared ventricular volumes and function, late gadolinium enhancement (LGE) and T1 relaxation times, between infected and non-infected elite athletes, and collected follow-up data on cardiac adverse events, ventricular arrhythmia burden and the cessation of sports careers.RESULTS: We included 259 elite athletes (mean age 26±5 years; 40% women), of whom 123 were infected (9% cardiovascular symptoms) and 136 were controls. We found no differences in function and volumetric CMR parameters. Four infected athletes (3%) demonstrated LGE (one reversible), compared with none of the controls. During the 26.7 (±5.8) months follow-up, all four athletes resumed elite-level sports, without an increase in ventricular arrhythmias or adverse cardiac remodelling. None of the infected athletes reported new cardiac symptoms or events. The majority (n=118; 96%) still participated in elite-level sports; no sports careers were terminated due to SARS-CoV-2.CONCLUSIONS: This prospective study demonstrates the safety of resuming elite-level sports after SARS-CoV-2 infection. The medium-term risks associated with SARS-CoV-2 infection and elite-level sports appear low, as the resumption of elite sports did not lead to detrimental cardiac effects or increases in clinical events, even in the four elite athletes with SARS-CoV-2 associated myocardial involvement.</p

Spatial Statistics of Visual Keypoints for Texture Recognition

recognitio

Kunnskapsgrunnlag for monetær verdsetting i økosystemregnskap. Vurdering av data og metode

Notatet viser resultatene fra en utredning av kunnskapsgrunnlaget for monetær verdsetting i økosystemregnskap på oppdrag fra Miljødirektoratet. Dette arbeidet er en del av en større utredning av hvordan et økosystemregnskap basert på FN sitt statistiske rammeverk (System of Environmental Economic Accounting Ecosystem Accounting – SEEA EA) kan implementeres i Norge. Formålet med å utvikle et økosystemregnskap for Norge er å styrke kunnskapsgrunnlaget både for internasjonal rapportering til FN og Eurostat og for naturforvaltning i Norge. Et økosystemregnskap i monetære verdier vil i hovedsak brukes til overvåkning og analyse av naturens bidrag til økonomien og samfunnet. Verdsetting av økosystemtjenester kan blant annet bidra til å synliggjøre betydningen av ikke-prisede økosystemtjenester for samfunnet slik som verdien av vannrensing, karbonopptak og -lagring og luftfiltrering og slik sammenstilles med andre varer og tjenester som vises i nasjonalregnskapet. Det vil kunne vise økonomiens avhengighet av økosystemtjenester som bidrag til verdiskaping, verdikjeder og endring over tid. Økosystem regnskapet kan også synliggjøre betydningen av naturgrunnlaget for forsynende økosystem tjenester fra jordbruk og skogbruk og fiske, allerede registrert i nasjonalregnskapet, og vise bidraget fra økosystemene. Økosystemregnskapet kan synliggjøre betydningen av kulturelle økosystem tjenester, som menneskers bruk av natur til friluftsliv, rekreasjon, læring og kunnskap. Undersøkelser fra Nederland og Storbritannia viser at de kulturelle økosystemtjenestene er betydelige. Verdsetting av økosystemtjenester kan også være viktig i analyser av arealendringer og for å synliggjøre kostnader og tap av økosystemtjenester. Kunnskapsgrunnlaget vil kunne bidra inn i beslutningsgrunnlaget for avveininger av arealdisponering og i vurdering av tiltak. Tallgrunnlaget vil kunne benyttes for å utarbeide planer, i forvaltningsarbeid og for å måle status. Utredningen har gått nærmere inn på verdsettingsmetoder som er i tråd ved prinsippene i nasjonal regnskapet og som kan benyttes ved monetær verdsetting av økosystemtjenester. Utredningen har videre sett på hvordan disse metodene kan benyttes til å beregne økosystemkapital. Andre verdsettingsmetoder utover nasjonalregnskapet har også blitt belyst for å bidra til et mer omfat tende kunnskapsgrunnlag for å vurdere naturverdier. For hver av økosystemtjenestene som er beskrevet i SEEA EA tabell 6.3 er det gitt en beskrivelse av mulige datagrunnlag for den biofysiske økosystemtjenesten, hvilke verdsettingsmetoder som er relevante og mulige datakilder. En vurdering av utfordringer, ressursbehov og forvaltningsnytte gis for de ulike kategoriene av økosystemtjenester og for ulike forvaltningsbehov. Notatet viser at det er stor ulikhet mellom økosystemtjenestene når det gjelder statistisk “modenhet” for mulig tallfesting. Enkelte kan på relativt kort sikt verdsettes på nasjonalt nivå. Dette gjelder for utvalgte forsyningstjenester der det allerede er et fullstendig datagrunnlag gjennom innrapportert statistikk. For andre tjenester mangler det enten et godt grunnlag for biofysisk vurdering eller også for monetær verdsetting. Det vil også være slik at økosystemregnskapet ikke kan omfatte grunnleggende naturverdier som ikke kan pris-settes. Verdsetting av økosystemtjenester, og videre arbeid med økosystemkapital og naturkapital, vil ha ulikt ambisjonsnivå og tilhørende behov for detaljnivå avhengig av om forvaltningsbehovet er på lokalt eller nasjonalt nivå. Det vil være behov for ytterligere utredninger for å avklare hvilke nivå man ønsker å etablere på kort og lang sikt, samt behov for kontakt med ulike interessenter og potensielle brukere av et regnskap for økosystemtjenester og et helhetlig økosystemregnskap. Oppdragsgiver: Miljødirektoratet, oppdragsgivers referanse M-2759|2024