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Images from ultrasound-guided regional anesthesia procedures can be difficult to interpret, especially by non-experts. In this work, deep convolutional neural networks were used to segment blood vessels, nerves and bone from two different nerve block procedures; the axillary nerve block and the femoral nerve block, which are commonly used to block sensation of pain from arms and legs respectively. The results show that the detection performance vary a lot for different nerves, with the best F1 and Dice scores of 0.84 and 0.67 for the median nerve, and the worst score of 0.54 and 0.51 for the ulnar nerve. Blood vessels and bone are generally easy to detect, but small veins can be difficult to segment accurately. Using the trained neural networks, a portable prototype system able to stream, process and visualize the results in real-time was created using a laptop, the FAST framework, and a Clarius L15 HD scanner. The runtime was measured to be about 31 milliseconds per frame.

Ultrasound-guided regional anesthesia can be challenging, especially for inexperienced physicians. The goal of the proposed methods is to create a system that can assist a user in performing ultrasound-guided femoral nerve blocks. The system indicates in which direction the user should move the ultrasound probe to investigate the region of interest and to reach the target site for needle insertion. Additionally, the system provides automatic real-time segmentation of the femoral artery, the femoral nerve and the two layers fascia lata and fascia iliaca. This aids in interpretation of the 2-D ultrasound images and the surrounding anatomy in 3-D. The system was evaluated on 24 ultrasound acquisitions of both legs from six subjects. The estimated target site for needle insertion and the segmentations were compared with those of an expert anesthesiologist. Average target distance was 8.5 mm with a standard deviation of 2.5 mm. The mean absolute differences of the femoral nerve and the fascia segmentations were about 1–3 mm.

Ultrasound images acquired during axillary nerve block procedures can be difficult to interpret. Highlighting the important structures, such as nerves and blood vessels, may be useful for the training of inexperienced users. A deep convolutional neural network is used to identify the musculocutaneous, median, ulnar, and radial nerves, as well as the blood vessels in ultrasound images. A dataset of 49 subjects is collected and used for training and evaluation of the neural network. Several image augmentations, such as rotation, elastic deformation, shadows, and horizontal flipping, are tested. The neural network is evaluated using cross validation. The results showed that the blood vessels were the easiest to detect with a precision and recall above 0.8. Among the nerves, the median and ulnar nerves were the easiest to detect with an [Formula: see text]-score of 0.73 and 0.62, respectively. The radial nerve was the hardest to detect with an [Formula: see text]-score of 0.39. Image augmentations proved effective, increasing [Formula: see text]-score by as much as 0.13. A Wilcoxon signed-rank test showed that the improvement from rotation, shadow, and elastic deformation augmentations were significant and the combination of all augmentations gave the best result. The results are promising; however, there is more work to be done, as the precision and recall are still too low. A larger dataset is most likely needed to improve accuracy, in combination with anatomical and temporal models.

Bacheloroppgave i Bedriftsutvikling for SMB fra Handelshøyskolen BI, 2017 Denne bacheloroppgaven i Bedriftsutvikling for SMB ble skrevet våren 2017 i samarbeid med matkasseleverandøren Godtlevert. I starten av semesteret kom vi tidlig i samtaler med bedriften om hva slags utfordringer de hadde, og hva de ønsket å vite mer om. Økonomisjefen, Christopher Ludt Parmo, var vår desidert største kontaktperson i Godtlevert. Han var svært klar på at lønnsomhet var et viktig fokus for Godtlevert fremover, og ikke kundevekst. Og etter å ha tatt dette i betraktning kom vi til slutt frem til en problemstilling: "Hva kan Godtlevert gjøre for å beholde kundemassen sin, og samtidig øke lønnsomheten?" Denne problemstillingen ble videre delt opp i fire delproblemstillinger, som til sammen løser hovedproblemstillingen. Disse problemstillingene dreide seg om kunnskap om markedet, kundelojalitet, mersalg og økonomi. I begynnelsen hadde vi liten kunnskap om trender, bransjen, kundene, konkurrentene og distribusjonen, og ønsket derfor å gjennomføre en markedsanalyse. Et av de åpenbare funnene var at matkassebransjen er i en regelrett enorm vekst. Kundeantallet har steget voldsomt de siste årene, og konkurrentene til Godtlevert øker omsetningen enormt. Godtlevert ønsket som nevnt ikke fokusere på å øke kundeandelen deres i markedet nevneverdig, og ønsket gjerne heller å øke mersalget fra nåværende kundemasse. Derfor foretok vi oss en spørreundersøkelse for å kunne se hva kundene mente om de ulike matkasseleverandørene, samt for å se om de hadde noen forslag til nye produkter. Godtlevert kom relativt godt ut av spørreundersøkelsen, og frokost og snacks var nye tilbud kundene ønsket. Godtlevert har nylig begynt med tilbudet "ukestart", så dette var noe Godtlevert allerede hadde tatt tak i. Videre delte vi inn kundene i ulike segmenter, og fant ut at Godtlevert ikke har et studenttilbud. Dekningsbidraget per matkasse ligger ifølge Christopher Ludt Parmo i gjennomsnitt på ca. 30 %, og en studentrabatt på 15-20 % kan dermed være lønnsom. Deretter analyserte vi økonomien og finansieringen til Godtlevert. Flere av funnene viste til svak lønnsomhet. Videre så kom vi med et forslag om å innføre en differensiert fraktkostnad som kunden betaler. Dette er et påfunn som kan møte motstand hos kundene, og ca. 53 % av respondentene i spørreundersøkelsen motsatte seg tiltaket. Dette konkluderte vi med at var lønnsomt antagelig på kort sikt, og høyst sannsynlig på lang sikt. Deretter drøftet vi kundelojalitet og hvilke faktorer som fremmer akkurat dette. Her ble det klart at god kundebehandling og kundetilfredshet på lang sikt vil føre til kundelojalitet. Derfor er det også viktig å ha dyktige og lojale medarbeidere som følger visjonen til ledelsen og Godtlevert. Videre så drøftet vi viktigheten av å ha fokus på riktige kunder, da dette er mest lønnsomt. Til slutt drøftes også belønninger i forhold til kundelojalitet. Den siste delproblemstillingen, mersalg, dreier seg om å få nåværende kunder til å handle for mer enn de alt gjør. Dermed drøftet vi tilleggsprodukter, rabatter, gratis fraktpris over 900 kroner og andre tiltak for å øke mersalget i en nettbasert forretning hvor kunden ikke kan bli overtalt av selgerne. Til slutt ble funnene i analysene, undersøkelsene og diskusjonen oppsummert i konklusjonsdelen. Her ble det også foretatt videre anbefalinger for Godtlevert.

BACKGROUND & AIMS: It is not clear how intake of gluten during infancy affects subsequent risk of celiac disease. We investigated whether gluten intake before 2 years of age increases risk for celiac disease in genetically susceptible children. METHODS: We performed a case-control study of 436 pairs of children, generated from a database of 2525 children with genetic susceptibility to celiac disease in Sweden, matched for sex, birth year, and HLA genotype from September 2004 and February 2010. Children were screened annually for celiac disease using an assay for tissue transglutaminase autoantibodies (tTGA). Intestinal biopsies were collected from children who tested positive for tTGA to confirm the presence of celiac disease. Gluten intake was calculated from 3-day food records collected when the children were 9, 12, 18 and 24 months old. RESULTS: Breastfeeding duration (median 32 weeks) and age at first introduction to gluten (median 22 weeks) did not differ between cases and tTGA-negative children (controls). At the visit prior to tTGA seroconversion, cases reported a larger intake of gluten (median 4.9 g/day) than controls (median 3.9 g/day) (odds ratio [OR], 1.28; 95% confidence interval [CI], 1.13-1.46; P=.0002). More cases consumed amounts of gluten in the upper 3rd tertile (i.e. >5.0 g/day) before they tested positive for tTGA seroconversion than controls (OR, 2.65; 95% CI, 1.70-4.13; P

BackgroundIncreased mammographic density is one of the strongest independent risk factors for breast cancer. It is believed that one third of breast cancers are derived from breasts with more than 50% density. Mammographic density is affected by age, BMI, parity, and genetic predisposition. It is also greatly influenced by hormonal and growth factor changes in a woman's life cycle, spanning from puberty through adult to menopause. Genetic variations in genes coding for hormones and growth factors involved in development of the breast are therefore of great interest. The associations between genetic polymorphisms in genes from the IGF pathway on mammographic density and circulating levels of IGF1, its binding protein IGFBP3, and their ratio in postmenopausal women are reported here.MethodsSamples from 964 postmenopausal Norwegian women aged 55-71 years were collected as a part of the Tromsø Mammography and Breast Cancer Study. All samples were genotyped for 25 SNPs in IGF1, IGF2, IGF1R, IGF2R, IGFALS and IGFBP3 using Taqman (ABI). The main statistical analyses were conducted with the PROC HAPLOTYPE procedure within SAS/GENETICS™ (SAS 9.1.3).ResultsThe haplotype analysis revealed six haploblocks within the studied genes. Of those, four had significant associations with circulating levels of IGF1 or IGFBP3 and/or mammographic density. One haplotype variant in the IGF1 gene was found to be associated with mammographic density. Within the IGF2 gene one haplotype variant was associated with levels of both IGF1 and IGFBP3. Two haplotype variants in the IGF2R were associated with the level of IGF1. Both variants of the IGFBP3 haplotype were associated with the IGFBP3 level and indicate regulation in cis.ConclusionPolymorphisms within the IGF1 gene and related genes were associated with plasma levels of IGF1, IGFBP3 and mammographic density in this study of postmenopausal women.