Koneoppimistekniikoiden soveltaminen radiografisten kuvien luokitteluun NDT-menetelmissä

Tiivistelmä. Tämän tutkielman tarkoituksena oli tutkia tekoälyn ja koneoppimisen tekniikoita teollisuuden NDT-menetelmien parissa. Tutkielman motiivina toimi NDT-tarkastajan tehtävässä hankkimani työkokemus ja sitä kautta syntynyt mielenkiinto alan uusimpia tekniikoita ja virtauksia kohtaan. NDT-menetelmistä keskityttiin erityisesti radiografiseen tarkastukseen ja radiografisten kuvien luokitteluun käytettävien koneoppivien algoritmien käyttöön. Tavoitteena oli tiedon lisääminen oppivien algoritmien mahdollisuuksista radiografisten kuvien tulkinnassa erityisesti pienillä opetusaineistoilla. Tutkielma toteutettiin kirjallisten lähteiden avulla, vertaamalla keskenään aiheesta toteutettuja tutkimuksia ja niistä saatuja tuloksia. Tutkielman tuloksena saatiin tietoa kolmen erilaisen algoritmin suorituskyvystä radiografisten kuvien luokittelussa ja vikojen segmentoinnissa. Tuloksista selvisi, että kahdella keskenään verratulla algoritmillä, tukivektorikoneella ja monikerrosperseptronilla, päästään keskenään liki samanlaisiin luokittelutuloksiin, tukivektorikoneen ollessa tuloksissa näistä kahdesta keskimäärin parempi algoritmi. Kolmantena mukana olleen syväoppivan konvolutiivisen neuroverkon tutkimustuloksissa keskityttiin pienimmän mahdollisen vikakoon löytämiseen kyseisen algoritmin avulla ja tutkimuksen mukaan menetelmä täyttää vaativimmatkin NDT-menetelmän herkkyydelle teollisuudessa asetetut vaatimukset. Tutkimusaineiston mukaan, koneoppivilla algoritmeillä on täydet valmiudet toimia tarkastajan apuna mm. vika-alueiden paikantamisessa, segmentoimisessa ja vikojen tilastoinnissa jo tällä hetkellä. Alan tutkimus on viime aikoina vahvasti painottunut konvolutiivisten neuroverkkojen suuntaan ja niiden merkitys teollisuuden NDT-menetelmien automatisoinnissa tulee epäilemättä olemaan näistä kolmesta koneoppivasta tekniikasta suurin

Ventilation during continuous compressions or at 30:2 compression-to-ventilation ratio results in similar arterial oxygen and carbon dioxide levels in an experimental model of prolonged cardiac arrest

Background: In refractory out-of-hospital cardiac arrest, transportation to hospital with continuous chest compressions (CCC) from a chest compression device and ventilation with 100% oxygen through an advanced airway is common practice. Despite this, many patients are hypoxic and hypercapnic on arrival, possibly related to suboptimal ventilation due to the counterpressure caused by the CCC. We hypothesized that a compression/ventilation ratio of 30:2 would provide better ventilation and gas exchange compared to asynchronous CCC during prolonged experimental cardiopulmonary resuscitation (CPR).Methods: We randomized 30 anaesthetized domestic swine (weight approximately 50 kg) with electrically induced ventricular fibrillation to the CCC or 30:2 group and bag-valve ventilation with a fraction of inspired oxygen (FiO(2)) of 100%. We started CPR after a 5-min no-flow period and continued until 40 min from the induction of ventricular fibrillation. Chest compressions were performed with a Stryker Medical LUCAS (R) 2 mechanical chest compression device. We collected arterial blood gas samples every 5 min during the CPR, measured ventilation distribution during the CPR using electrical impedance tomography (EIT) and analysed post-mortem computed tomography (CT) scans for differences in lung aeration status.Results: The median (interquartile range [IQR]) partial pressure of oxygen (PaO2) at 30 min was 110 (52-117) mmHg for the 30:2 group and 70 (40-171) mmHg for the CCC group. The median (IQR) partial pressure of carbon dioxide (PaCO2) at 30 min was 70 (45-85) mmHg for the 30:2 group and 68 (42-84) mmHg for the CCC group. No statistically significant differences between the groups in PaO2 (p =0.40), PaCO2 (p = 0.79), lactate (p = 0.37), mean arterial pressure (MAP) (p = 0.47) or EtCO2 (p = 0.19) analysed with a linear mixed model were found. We found a deteriorating trend in PaO2, EtCO2 and MAP and rising PaCO2 and lactate levels through the intervention. There were no differences between the groups in the distribution of ventilation in the EIT data or the post-mortem CT findings.Conclusions: The 30:2 and CCC protocols resulted in similar gas exchange and lung pathology in an experimental prolonged mechanical CPR model.Peer reviewe

Non-Hodgkin lymphoma response evaluation with MRI texture classification

<p>Abstract</p> <p>Background</p> <p>To show magnetic resonance imaging (MRI) texture appearance change in non-Hodgkin lymphoma (NHL) during treatment with response controlled by quantitative volume analysis.</p> <p>Methods</p> <p>A total of 19 patients having NHL with an evaluable lymphoma lesion were scanned at three imaging timepoints with 1.5T device during clinical treatment evaluation. Texture characteristics of images were analyzed and classified with MaZda application and statistical tests.</p> <p>Results</p> <p>NHL tissue MRI texture imaged before treatment and under chemotherapy was classified within several subgroups, showing best discrimination with 96% correct classification in non-linear discriminant analysis of T2-weighted images.</p> <p>Texture parameters of MRI data were successfully tested with statistical tests to assess the impact of the separability of the parameters in evaluating chemotherapy response in lymphoma tissue.</p> <p>Conclusion</p> <p>Texture characteristics of MRI data were classified successfully; this proved texture analysis to be potential quantitative means of representing lymphoma tissue changes during chemotherapy response monitoring.</p

Physical inactivity from youth to adulthood and adult cardiometabolic risk profile

Adults with a low physical activity (PA) level are at increased risk for cardiometabolic diseases, but little is known on the association between physical inactivity since youth and cardiometabolic health in adulthood. We investigated the association of persistent physical inactivity from youth to adulthood with adult cardiometabolic risk factors. Data were drawn from the ongoing Cardiovascular Risk in Young Finns Study with seven follow-ups between 1980 and 2011 (baseline age 3–18 years, n = 1961). Physical activity data from a standardized questionnaire was expressed as a PA-index. Using the PA-index, four groups were formed: 1)persistently physically inactive (n = 246), 2)decreasingly active (n = 305), 3)increasingly active (n = 328), and 4)persistently active individuals (n = 1082). Adulthood cardiometabolic risk indicators included waist circumference, body mass index (BMI), blood pressure, and fasting lipids, insulin, and glucose. Clustered cardiometabolic risk was defined using established criteria for metabolic syndrome. Persistently physically inactive group was used as a reference. Compared to the persistently physically inactive group, those who were persistently active had lower risk for adult clustered cardiometabolic risk (RR = 0.67;CI95% = 0.53–0.84; Harmonized criteria), obesity (BMI > 30 kg/m2, RR = 0.76;CI95% = 0.59–0.98), high waist circumference (RR = 0.82;CI95% = 0.69–0.98), and high triglyceride (RR = 0.60;CI95% = 0.47–0.75), insulin (RR = 0.58;CI95% = 0.46–0.74) and glucose (RR = 0.77;CI95% = 0.62–0.96) concentrations as well as low high-density lipoprotein cholesterol (HDLsingle bondC) concentration (RR = 0.78;CI95% = 0.66–0.93). Comparable results were found when persistently physically inactive individuals were compared with those who increased PA. The results remained essentially similar after adjustment for education, diet, smoking, and BMI. Persistently physically inactive lifestyle since youth is associated with an unfavorable cardiometabolic risk profile in adulthood. Importantly, even minor increase in PA lowers the cardiometabolic risk.peerReviewe