MedViz – a Research & Development cluster in Bergen. MedViz is a cluster of groups performing interdisciplinary research in advanced image analysis and visualisation bridging the gap between “bench and bedside”. MedViz also includes imaging physics and fundamental biomedical translational research. Our mission is to promote the development of biomedical and clinical imaging technologies with the ultimate goal of improving diagnosis and treatment of patients. MedViz wants to develop new clinical methods for potential commercialisation by means of denovo software for analysis, decision support and visual communication.
VCF 22.03.2013

Real-time segmentation of 3D echocardiograms, using a state estimation approach with deformable models

We would like to invite you at the next Visual Computing Forum seminar, which will be held on Friday, March 22. The seminar will take place from 10.15 to 11.15. at the Høyteknologisenteret, datablokk, in the Lille Auditorium at the second floor.
Our speakers will be Fredrik Orderud (R&D engineer, GE Vingmed Ultrasound - GE Healthcare), and he will present his work on segmentation of 3D echocardiograms based on deformable models.
You can find more details in the enclosed flyer or on our website:
We hope to see you all on Friday
With best regards, The Visualization Group
Last Updated on Thursday, 21 March 2013 07:39
NORSTROKE [In Norwegian]


Bergen Stroke Research Group                                                                                            

Bergen, 21.03.2013


Forskningsprosjekt: Hva skjer i hjernen etter et slag?


Vi søker etter friske høyrehendte menn som er 46, 73, 81 år gamle og kvinner som er 56 år gamle og villige til å delta i et nevro-vitenskapelig forskningsprosjekt for å belyse funksjonelle og strukturelle forandringer i hjernen etter et hjerneslag.


Prosjektet består i å gjennomgå MR-undersøkelse og nevropsykologisk testing 3 ganger. Hver undersøkelsesrunde tar ca. 2 timer og gjennomføres i helgene.


Undersøkelsene medfører ingen helserisiko. Data blir lagret anonymisert og vil bli delt med forsøkspersonen og/eller fastlege, bare dersom det er en medisinsk grunn til det.


Studien er godkjent av Regional komité for medisinsk forskningsetikk.

Prosjektleder er Professor Lars Thomassen, Nevrologisk avdeling, Haukeland Universitetssykehus.



Dersom du er villig til å hjelpe oss, kontakt Stipendiat Judit Haász MD          

e-post:             This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Telefon:          55 97 50 45 (ekspedisjonen, nevrologisk avdeling)

Last Updated on Thursday, 21 March 2013 08:52
Publication of the Month, March

Assessment of Kidney Volumes From MRI: Acquisition and Segmentation Techniques

Frank G.Zöllner1 2, Einar Svarstad3, Antonella Z. Munthe-Kaas4, Lothar R. Schad1, Arvid Lundervold5 6 and Jarle Rørvik2 6
OBJECTIVE. The prevalence of chronic kidney disease (CKD) is increasing worldwide. In Europe alone, at least 8% of the population currently has some degree of CKD. CKD is associated with serious comorbidity, reduced life expectancy, and high economic costs; hence, early detection and adequate treatment of kidney disease are important.
CONCLUSION. We review state-of-the-art MRI acquisition techniques for CKD, with a special focus on image segmentation methods used for the estimation of kidney volume.
New imaging modalities have achieved an increasingly important role in the clinical workup of chronic kidney diseases (CKDs). They allow minimally invasive measurement of the kidney volume and the loss of functional parenchyma, as well as renal blood flow (RBF) and glomerular filtration rate (GFR). Sonography is a standard low-cost modality and is easily accessible. However, it is operator dependent, estimated volumes suffer from poor reproducibility and low accuracy, and 3D ultrasound equipment is not widely available. CT provides precise measurements, also in 3D, but the patients are exposed to ionized radiation and iodinated contrast agents, which
may be contraindicated for use. MRI may emerge as a good alternative by acquiring high-resolution 3D images without radiation exposure. Generally, MRI provides good tissue contrast that facilitates segmentation of the kidney and extraction of volumetric information from the images. Methods for performing such segmentation range from simple manual delineation to the application of advanced object-detection algorithms. Image data acquired by these methods comprise purely morphologic T1- or T2-weighted images as well as contrast-enhanced and time-resolved image data. In the present review, state-of-the-art methods of acquisition and segmentation for performing
high-quality renal volumetry by MRI will be discussed.
Last Updated on Tuesday, 12 March 2013 16:55
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