Aptit

Aptit och hunger initierar ätandet. Aptiten påverkas av våra sinnesintryck men även det som tillfredsställer våra psykologiska, sociala, och kulturella behov kan inverka positivt på aptiten. Hungern stimuleras bland annat av sammandragningar i magsäcken, blodsockernivån, frånvaron av näring i tunntarmen och mag- tarmkanalens hormoner. Hög fysisk aktivitet ökar förbränningen och stimulerar därmed hungern. Den behagliga upplevelsen av mättnad utlöses av att det finns näring i tunntarmen, vilket frigör hormoner som signalerar mättnad. Med stigande ålder försämras förmågorna att känna lukt och smak. Eftersom luktupplevelsen har stor betydelse för smaken påverkas hela den sensoriska upplevelsen av maten. Därför behövs större koncentrationer av smaker för att ge samma upplevelse som när man var yngre. Upplevelsen av smak och lukt påverkas också negativt av läkemedelsintag. Äldre upplever även törst i mindre omfattning än yngre och känner inte samma välbehag i att släcka törsten och har därför ett mindre intag av drycker. Minskad fysisk aktivitet minskar aptiten och energibehovet, men trots minskat energibehov kvarstår behovet av näringsämnen relativt konstant. "Aptiten på mat" påverkas också av att vistas på institution. Ändrade måltidsmönster och maträtter gör att det är lätt att känna sig obekväm och då blir aptiten sämre. Man får obehagskänslor vi matbordet

SEGMENTING TAGGED CARDIAC MRI DATA USING A LOCAL VARIANCE FILTER

We present a new method for segmenting tagged MRI data. It is based on the observation that the tagging grid vanishes almost immediately inside the ventricles because of the blood flow. Segmentation can be therefore driven by the intensity of the tagging grid. We estimate the intensity using a local variance filter. The main segmentation is computed by the graph-cuts method, though other segmentation methods can also be used. We compare the results obtained by our method with manual segmentation

Application of a degenerate deffusion method in medical image processing

MI: Global COE Program Education-and-Research Hub for Mathematics-for-IndustryグローバルCOEプログラム「マス･フォア･インダストリ教育研究拠点」This paper deals with segmentation of image data using a partial differential equation of level-set type. The first part of this paper describes the level-set formulation and modification of the level-set equation. The evolution process are controlled by the segmented image data in such a way that the edges of objects can be found. The semi-implicit complementary-volume numerical scheme is used for solving the level-set equation. The final part of the paper describes algorithm parameters and their setting used for segmentation of the left heart ventricle in the cardiac MRI images

Application of a degenerate deffusion method in medical image processing

This paper deals with segmentation of image data using a partial differential equation of level-set type. The first part of this paper describes the level-set formulation and modification of the level-set equation. The evolution process are controlled by the segmented image data in such a way that the edges of objects can be found. The semi-implicit complementary-volume numerical scheme is used for solving the level-set equation. The final part of the paper describes algorithm parameters and their setting used for segmentation of the left heart ventricle in the cardiac MRI images.MI: Global COE Program Education-and-Research Hub for Mathematics-for-IndustryグローバルCOEプログラム「マス･フォア･インダストリ教育研究拠点

Magnetic Resonance Imaging of the Heart and Large Vessels -- Survey of methods and new perspectives

International audienceEarly cardiac magnetic resonance imaging (CMR) scans were of inferior quality. A sig- ni cant improvement in image quality was achieved a er introducing the segmented acquisition of the k-space synchronized with patient’s ECG, performed either in breath hold or free breathing. CMR is now used widely in the clinical setting for assessment of cardiac chamber volumes, global and regional cardiac contraction, morphology and tissue charac- terization. In ammatory or post- myocardial infarction changes involve sequences which can appreciate myocardial edema or the use of late post-gadolinium contrast enhancement (LGE) to visualise di use or focal scar. Other applications include the assessment of valvular stenosis or regurgitation by means of ow me- asurement through a de ned ori ce and rst pass myocardial perfusion to assess ischemia. Last but not least, CMR is increasingly used for the assessment of congenital heart diseases, in which CMR o ers objective and directly com- parable measures during serial examinations, without any radiation exposure

Signed-distance function based non-rigid registration of image series with varying image intensity

International audienceIn this paper we propose a method for locally adjusted optical flow-based registration of multimodal images, which uses the segmentation of the object of interest and its representation by the signed-distance function (OF dist method). We deal with non-rigid registration of the image series acquired by the Modiffied Look-Locker Inversion Recovery (MOLLI) magnetic resonance imaging sequence, which is used for a pixel-wise estimation of T 1 relaxation time. The spatial registration of the images within the series is necessary to compensate the patient's imperfect breath-holding. The evolution of intensities and a large variation of image contrast within the MOLLI image series, together with the myocardium of left ventricle (the object of interest) typically not being the most distinct object in the scene, makes the registration challenging. The paper describes all components of the proposed OF dist method and their implementation. The method is then compared to the performance of a standard mutual information maximization-based registration method, applied either to the original image (MIM) or to the signed-distance function (MIM dist). Several experiments with synthetic and real MOLLI images are carried out. On synthetic image with a single object, MIM performed the best, while OF dist and MIM dist provided better results on synthetic images with more than one object and on real images. When applied to signed-distance function of two objects of interest, MIM dist provided a larger registration error (but more homogeneously distributed) compared to OF dist. For the real MOLLI image series with left ventricle pre-segmented using a level-set method, the proposed OF dist registration performed the best, as is demonstrated visually and by measuring the increase of mutual information in the object of interest and its neighborhood