Inledning: Den svenska träningstrenden fortsätter enligt stadiums årliga undersökning om svenskarnas träningsvanor. Enligt Livsmedelsverket är kosttillskott ett komplement som ska konsumeras utöver den vanliga kosten, och motiveringen till att idrottare använder kosttillskott är exempelvis för att skydda hälsa och prestation. Proteintillskott konsumeras för att öka proteinsyntesen och påverkar muskelfunktioner och träning positivt. Studier har tidigare undersökt atleters inställning till kosttillskott, men få studier har undersökt inställningen till proteintillskott hos människor som har styrketräning som ett fritidsintresse.       Syfte: Studien avser att undersöka inställningen till användandet av kosttillskott i form av protein (proteinpulver, bars). Studien ska också undersöka proteinintaget hos användare och icke-användare av proteintillskott.   Material och metod: Studien utgjordes av en webbaserad enkät och en kostregistrering. Inklusionskriterierna för att delta i studien var att träna minst tre gånger i veckan, vara man och minst 18 år gammal. Rekryteringen genomfördes via en Facebook grupp som riktar sig mot dom som har ett intresse för träning och hälsa.    Resultat: Totalt deltog tio personer i kostregistreringen. Det förekom underrapportering av energiintaget i samtliga kostregistreringar, vilket påverkar resultatets trovärdighet. Det fanns en viss skillnad i proteinintaget mellan användare och icke-användare av proteintillskott, och icke-användare av proteintillskott konsumerade mer animalieprodukter än användare. Det var 26 personer som besvarade enkäten, och var mellan 18–50 år gamla och tränade minst tre gånger i veckan på gym. Svarsfrekvensen på frågorna varierade eftersom det var öppna frågor. Anledningen för att använda proteintillskott är att få i sig extra protein, och anledningen för att inte använda proteintillskott är för att de får i sig tillräckligt med protein från den vardagliga kosten.   Slutsats: Trots osäkerheten i rapporterade data av energiintaget visar kostregistreringarna att användare av proteintillskott till stor del förlitar sig på att proteintillskott täcker proteinbehovet, och konsumtions skillnaden av olika typer av livsmedelsgrupper var framförallt animalieprodukter. Anledningen till att avstå från proteintillskott är huvudsakligen på grund av kostnaden och dess effekt. / Introduction: The Swedish training trend continues according to Stadiums annual survey of Swedes' training habits. Dietary supplements are a supplement that should be consumed in addition to the usual diet, and the motivation for athletes to use dietary supplements is, for example, to protect health and performance. Protein supplements are consumed to increase protein synthesis and positively affect muscle function and exercise. Studies have previously examined athletes' attitudes towards dietary supplements, but few studies have examined the attitude towards protein supplements in people who have weight training as a hobby.     Aim: The study aims to investigate the attitude to the use of dietary supplements in the form of protein (protein powder, bars). The study will also examine the protein intake of users and non-users of protein supplements.   Material and method: The study consisted of a web-based questionnaire and a diet registration. The recruitment was carried out via a Facebook group that focuses on exercise and health.   Results: A total of ten people participated in the diet registration. There was underreporting of energy intake in all diet registrations, which affects the credibility of the results. There was some difference in protein intake between users and non-users of protein supplements, and non-users of protein supplements consumed more animal products than users. A total of 26 people answered the web formula questionnaire from 18 years up to 50 years old and trained at least three times per week, the response rate varied as there were open ended questions. Intake of protein supplements is largely due to the fact that you need to get extra protein and for those who choose to abstain, it was more about they got enough from their everyday diet.     Conclusion: Despite the uncertainty in reported data on energy intake, dietary records show that users of protein supplements largely rely on protein supplements to cover protein requirements, and the difference in consumption of different types of food groups was primarily animal products. The reason for refraining from protein supplements is because of the cost and its effect.

The prospective student who has been accepted and who fails to arrive on the college campus despite his apparent intentions presents a problem to secondary school principals as well as to college officials. Non-arrivals are common on the admissions records of every college or university. (14) Alden B. Threasher reports admissions attrition percentages ranged from 3 percent to 55 percent with averages of 27 percent to 46 percent in a study of 58 institutions grouped by type.

Indiana University-Purdue University Indianapolis (IUPUI) / Adaptive Optics Optical Coherence Tomography (AO-OCT) is a high-speed, high-resolution ophthalmic imaging technique offering detailed 3D analysis of retina structure in vivo. However, AO-OCT volume images are sensitive to involuntary eye movements that occur even during steady fixation and include tremor, drifts, and micro-saccades. To correct eye motion artifacts within a volume and to stabilize a sequence of volumes acquired of the same retina area, we propose a stripe-wise 3D image registration algorithm with phase correlation. In addition, using several ideas such as coarse-to-fine approach, spike noise filtering, pre-computation caching, and parallel processing on a GPU, our approach can register a volume of size 512 x 512 x 512 in less than 6 seconds, which is a 33x speedup as compared to an equivalent CPU version in MATLAB. Moreover, our 3D registration approach is reliable even in the presence of large motions (micro-saccades) that distort the volumes. Such motion was an obstacle for a previous en face approach based on 2D projected images. The thesis also investigates GPU implementations for 3D phase correlation and 2D normalized cross-correlation, which could be useful for other image processing algorithms.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第19225号 / 医博第4024号 / 新制||医||1010(附属図書館) / 32224 / 京都大学大学院医学研究科医学専攻 / (主査)教授 戸井 雅和, 教授 富樫 かおり, 教授 一山 智 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DGAM

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Deformable image registration is usually performed manually by clinicians,which is time-consuming and costly, or using optimization-based algorithms, which are not always optimal for registering images of different modalities. In this work, a deep learning-based method for MR-CT deformable image registration is presented. In the first place, a neural network is optimized to register CT pelvic image pairs. Later, the model is trained on MR-CT image pairs to register CT images to match its MR counterpart. To solve the unavailability of ground truth data problem, two approaches were used. For the CT-CT case, perfectly aligned image pairs were the starting point of our model, and random deformations were generated to create a ground truth deformation field. For the multi-modal case, synthetic CT images were generated from T2-weighted MR using a CycleGAN model, plus synthetic deformations were applied to the MR images to generate ground truth deformation fields. The synthetic deformations were created by combining a coarse and fine deformation grid, obtaining a field with deformations of different scales. Several models were trained on images of different resolutions. Their performance was benchmarked with an analytic algorithm used in an actual registration workflow. The CT-CT models were tested using image pairs created by applying synthetic deformation fields. The MR-CT models were tested using two types of test images. The first one contained synthetic CT images and MR ones deformed by synthetically generated deformation fields. The second test set contained real MR-CT image pairs. The test performance was measured using the Dice coefficient. The CT-CT models obtained Dice scores higherthan 0.82 even for the models trained on lower resolution images. Despite the fact that all MR-CT models experienced a drop in their performance, the biggest decrease came from the analytic method used as a reference, both for synthetic and real test data. This means that the deep learning models outperformed the state-of-the-art analytic benchmark method. Even though the obtained Dice scores would need further improvement to be used in a clinical setting, the results show great potential for using deep learning-based methods for multi- and mono-modal deformable image registration.

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A substantial fraction of the automotive assembly comprises formed sheet metal parts. To reduce vehicle weight and improve fuel economy, total sheet metal mass should be minimized without compromising the structural integrity of the vehicle. Excessive deformation contributes to tearing or buckling of the metal, and therefore a forming limit is investigated experimentally to determine the extent to which each particular material can be safely strained. To assess sheet metal formability, this thesis proposes a novel framework for sheet metal surface strain measurement using a scalable dot-grid pattern. Aluminum sheet metal samples are marked with a regular grid of dot-features and imaged with a close-range monocular vision system. After forming, the sheet metal samples are imaged once again to examine the deformation of the surface pattern, and thereby resolve the material strain. Grid-features are localized with sub-pixel accuracy, and then topologically mapped using a novel algorithm for deformation-invariant grid registration. Experimental results collected from a laboratory setup demonstrate consistent robustness under practical imaging conditions. Accuracy, repeatability, and timing statistics are reported for several state-of-the-art feature detectors. / Thesis / Master of Applied Science (MASc)

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Video from aerial surveillance can provide a rich source of data for analysts. From the time-critical perspective of wilderness search and rescue operations, information extracted from aerial videos can mean the difference between a successful search and an unsuccessful search. When using low-cost, payload-limited mini-UAVs, as opposed to more expensive platforms, several challenges arise, including jittery video, narrow fields of view, low resolution, and limited time on screen for key features. These challenges make it difficult for analysts to extract key information in a timely manner. Traditional approaches may address some of these issues, but no existing system effectively addresses all of them in a unified and efficient manner. Building upon a hierarchical dense image correspondence technique, we create a unifying framework for reducing jitter, enhancing resolution, and expanding the field of view while lengthening the time that features remain on screen. It also provides for easy extraction of moving objects in the scene. Our method incorporates locally adaptive warps which allows for robust image alignment even in the presence of parallax and without the aid of internal or external camera parameters. We accelerate the image registration process using commodity Graphics Processing Units (GPUs) to accomplish all of these tasks in near real-time with no external telemetry data.