De-identification of medical images using object-detection models, generative adversarial networks and perceptual loss

Medical images play an essential role in the process of diagnostics and detection of a variety of diseases. Whether it being anatomical features or molecular cells, medical imaging help visualize and gain insight into the human body. These images are a crucial aid in the process of diagnosing patients. While these images are informative, they can also be quite difficult to interpret, necessitating highly trained medical professionals to read the images. The amount of medical images produced is enormous compared to the amount of professionals whose task it is to interpret them. The diagnosis can also vary based on the medical professional who inspects the image. The recent rise of a new generation of Computer Aided Detection (CAD) systems based on machine learning has become more and more important to battle this problem. These systems aids the medical professional in the diag- nostic process. This can lead to a more consistent and accurate interpretations of medical images by removing some human bias. In addition, such systems can be used to decrease the workload by either filtering out images deemed as belonging to healthy subjects, to be otherwise not of interest, or marking images as indicating a risk. When creating CAD systems utilizing machine learning you are very de- pendent on data. Since the systems will typically be placed in very delicate, high-risk situations, the quality of the data is always a priority. A common problem in medical imaging research is not getting sufficient data. Not that there is a shortage of images, but to be used in research, they typically have to be de-identified or anonymized. This process has to be verified manually and is therefore time-consuming. With the impressive advancement of machine learning in recent decades, it seems natural to attempt de-identification using machine learning, especially because several powerful models are being applied to similar tasks in other fields. One key reason for the success of machine learn- ing is its ability to detect and generate patterns. Currently, there are several applications that perform de-identification by placing black-boxes on top of in- formation detected as being sensitive [1, 2]. However, the black boxes can end up hiding also other parts of the image, but ideally all non-sensitive features in the image should be preserved. In this thesis we investigate the effect of using image-to-image deep learning to automate 2D medical image de-identification by detecting the sensitive information, and removing it without the use of black boxes. Our results indicate that de-identification models based on machine learning can result in viable and powerful solutions. The deep learning models manage to accurately detect and remove text, without large negative impact on the original image.Masteroppgave i Programutvikling samarbeid med HVLPROG399MAMN-PRO

Inconsistencies in the pozzolanic strength activity index (SAI) for silica fume according to EN and ASTM

Published version of an article in the journal: Materials and Structures. Also available from the publisher at: http://dx.doi.org/10.1617/s11527-014-0457-6 Open AccessNew supplementary cementitious materials claimed to possess pozzolan properties emerge frequently. This development is driven both by economic and environmental pressures. Properties of new materials are compared with those of materials already well known, such as silica fume. Several test methods are standardized for making such comparisons, regulated by both European (EN) and American (ASTM) standards. Standardization indicates that procedures are secured to make comparisons valid and informative. In this article the sensitivity of accepted variations within each of the standard procedures are investigated to determine if the results are influenced by such variations. Various methods for testing pozzolanic properties are briefly discussed. Experimental work was carried out in compliance with the standard methods for testing silica fume, according to both EN and ASTM. Seventy two mixes are made and tested in the experimental series, combining two standard procedures, two types of sand, three cements and four flow agents (SP). The results show that determined values are highly influenced by variations accepted to be made within the standard procedures. Possible reasons for these variations are analyzed. Conclusions are made that even when complying with the standards, the results are heavily manipulable (intended or unintended). Also a shortcoming in EN regarding new materials, is detected. Suggestions are made on additional information required to be given together with the results when reporting pozzolanic properties according to standards in order to make results informative and reproducible. A limitation in EN towards testing nano-sized silica materials is detected. An adjustment is suggested, to make EN applicable correspondingly to ASTM, also for these materials

Writing in Britain and Ireland, c. 400 to c. 800

No abstract available

Sentralbankens likviditetspolitikk i en oljeøkonomi

Gjennom likviditetspolitikken sørger Norges Bank for at bankene til enhver tid har tilstrekkelig store innskudd i Norges Bank. De kortsiktige pengemarkedsrentene vil da bli liggende like over styringsrenten, som er renten på bankenes innskudd i Norges Bank. Norges Bank bruker auksjoner av lån som instrument i likviditetspolitikken. Ordningen for kanalisering av statens petroleumsinntekter til Statens pensjonsfond – Utland spiller en stor rolle for gjennomføringen av likviditetspolitikken. Likviditetspolitikken har også en rolle ved uro i finansmarkedene

Renter og rentemarginer

Norges Bank setter styringsrenten. Pengemarkedsrentene påvirkes av styringsrenten og av forventninger om fremtidig styringsrente. Endringer i styringsrenten og pengemarkedsrentene påvirker bankenes innskudds- og utlånsrenter. I dette notatet drøftes om dette skyldes ulikt tidsforløp (tidslag) mellom disse rentene og om tidslag påvirker forløpet av fordelingen av rentemarginen mellom utlånsmargin og utlånsmargin. Vi drøfter først bakgrunnen for forskjellen i tidsforløp mellom pengemarkedsrenten og styringsrenten og deretter bakgrunnen for forskjellen i tidsforløp mellom styringsrenten og utlånsrenten. Ut fra dette trekker vi en konklusjon om forskjellen i tidsforløp mellom pengemarkedsrenten og utlånsrenten. På bakgrunn av resultatene av denne analysen introduserer vi tidslag mellom de ulike rentene. Med tidslag viser de ulike rentene et vesentlig mer parallelt forløp enn uten tidslag

Effective Quantification of the Paper Surface 3D Structure

This thesis covers the topic of image processing in relation to the segmentation and analysis of pores protruding the surface in the three dimensional surface structure of paper. The successful analysis of pores is related to a greater goal of relating such an analysis to the perceived quality of the surface of a paper sample. The first part of the thesis gives an introduction to the context of image processing in relation to paper research. Also, an overview of the image processing framework used for image processing plugin development, ImageJ, is provided, together with the current status of ImageJ plugins for surface characterization. The second part of the thesis gives an overview of an envisioned future paper quality assessment system. The quality assesment system described consists of six phases, three of which are treated in this thesis. These are the Image Processing phase, the Modeling phase, and the Measurement phase. The Image Processing phase is further divided into three subphases. These are the Error Correction subphase, the Pore Extraction subphase, and the Segmentation phase. Together with the description of the phases of the system, techniques are presented that are relevant to the phase currently being described. The third part of the thesis covers the development of new plugins for surface characterization within the ImageJ framework. Examples are given and evaluated to show the usage and results of each plugin, and each plugin is related to a specific part of the quality assesment system. Also, a tutorial covering use of several plugins in sequence is presented. The parts of the system receiving the most attention in relation to plugin development are segmentation and modeling

The Central Bank’s Liquidity Policy in an Oil Economy

Norges Bank’s instrument for achieving the objective of low and stable inflation is the key policy rate – the rate of interest on banks’ deposits in Norges Bank. But how do Norges Bank’s interest rate decisions affect market interest rates? They work through liquidity policy. The aim of liquidity policy is to ensure that banks always have sufficient deposits in Norges Bank so that short-term money market rates remain just above the interest rate on banks’ deposits in Norges Bank. Norges Bank uses auctions of F-loans – fixed-rate loans with varying maturities issued against collateral – as its liquidity policy instrument. The system for channelling government petroleum revenues into the Government Pension Fund – Global plays a major role in the implementation of liquidity policy. Liquidity policy also has a part to play in the event of turbulence in financial markets

Hip Hop-Feminisme: Et provokativt, svett og rytmisk innlegg i den kontemporære debatten om feminisme

Feministisk-kritiske forfattere innen akademia, argumenterer for hvordan kvinnelig rap kan plasseres innen en større svart feministisk musikalsk kontekst, der etnisitet, kjønn og seksualitet blir diskutert i et styrkende og selv-representativt format. På midten av 1990-tallet, ved oppblomstringen av en tredje feministisk bølge, ble akademiske tekster om musikk og svart feministisk epistemologi utfordret vedrørende budskap omkring svart kvinnelig seksualitet og kvinnerollen. Det var en av de virkende årsakene til fremveksten av den feministiske retningen kalt hip hop-feminisme, som utforsker effekten og konsekvensene av å engasjere hip hop-kultur, rap-musikk og feminisme. Denne oppgaven ser nærmere på hip hop-feminismens sosiopolitiske agenda, ved å analysere musikalsk tekst og visuell estetikk hos kvinnelige hip hop-artister; Missy Elliott og Cardi B. Dette basert på relevante akademiske tekster om svart kvinnelig seksualitet, andre og tredje bølge feminisme, og ‘male gaze’. Ved tidsforskjellen mellom de to artistenes storhetstid, forsøker teksten å si noe om endringene som har skjedd innen hip hop-kultur, i tiden fra 1990-tallet fram til i dag. Oppgaven er en gjennomgående diskusjon hva hip hop-feminisme kan tilføye i samfunnsmessige debatter vedrørende etnisitet, kjønn og seksualitet