Successful Master thesis defence of Luka Rogelj and Doroteja Novak

On Wednesday, 6/9/2017, our future young researcher Luka Rogelj completed his studies with Master’s thesis titled “Magnetic resonance imaging of samples with short relaxation time T2” and obtained the title of Master of Medical Physics.
On Thursday, 14/9/2017, our new research group member and young researcher Doroteja Novak successfully completed her studies at the Faculty of Pharmacy. With her work titled “Design and synthesis of novel bacterial DNA gyrase A inhibitors”, she obtained a Master’s degree in pharmacy with cum laude honors.

Congratulations!

Luka Doroteja

Journal Club #14

On Wednesday, May 31, Urban Simončič will present a paper titled A hybrid patient-specific biomechanical model based image registration method for the motion estimation of lungs. You can find the article here. We start at 11 AM in lecture room F4.

See you there!

immuno

Journal club #13

On Wednesday, May 17, Nina Verdel will present a paper titled In Vivo Multiphoton-Microscopy of Picosecond-Laser-Induced Optical Breakdown in Human Skin. You can read the article here. We start at 11 AM in lecture room F4.

fluorescenca

Lecture by Ivan Štajduhar

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On Wednesday, May 10th, 2017 at 16:00, assoc. prof. Ivan Štajduhar (Department of Computer Engineering, University of Rijeka – Faculty of Engineering) will give a lecture titled Artificial Intelligence in Medicine. The lecture will be held in lecture hall F2 (first floor) in the physics department building, Jadranska 19, Ljubljana.

Artificial Intelligence in Medicine
Would it be possible to supersede physicians with computers, to some extent, at least? The idea of computer-aided diagnosis in diagnosing and treating illnesses has been around from nineteen-eighties. It was then that scientists discovered that, by applying statistical algorithms on real-world patient data, using so-called machine learning, one can establish useful (almost-)out-of-the-box mathematical models that perform well at describing some problems. In the last decade, significant increases occurred worldwide in the level of informatics-readiness of clinical centres, in the availability of standardised technology for data exchange and storage, and in the abundance of quality medical radiology techniques. This, in turn, resulted in an explosion in the availability of voluminous data, enabling further advances in the field of computer-aided diagnosis and treatment. In this lecture, in addition to some fundamentals related to the field, several topics concerning medical image analysis will be discussed: learning predictive models for diagnosing knee injury, data preprocessing for reducing model complexity and transfer learning in medical radiology domain (“RadiologyNet”, a research project conducted in collaboration with the Clinical Hospital Centre Rijeka, Croatia).