Mrs. Diana Sitarcikova, Medical University Vienna, Austria
Diana Sitarcikova (née Bencikova) is a dedicated PhD student specializing in medical physics at the Medical University of Vienna. With a strong foundation in biomedical physics, she has developed expertise in advanced imaging techniques, including MRI and liver evaluation. Her research focuses on multi-parametric non-invasive diagnostic methods, combining texture analysis and machine learning to enhance diagnostic accuracy in radiology. Diana’s academic journey began at Comenius University in Bratislava, where she completed her bachelor’s and master’s degrees. She has co-authored numerous publications in esteemed journals, showcasing her contributions to liver and cartilage imaging. Proficient in Python, R, and MATLAB, Diana is skilled in data analysis, machine learning, and image processing. Her linguistic abilities in Slovak, English, and German further enrich her collaborative potential. Committed to innovation, Diana actively participates in international conferences and workshops, advancing her knowledge and sharing her expertise in the evolving field of biomedical imaging.
Professional Profile
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Evaluation of Diana Sitarcikova for the Research for Best Researcher Award
Summary of Suitability: Diana Sitarcikova, an accomplished researcher in the field of biomedical imaging and medical physics, demonstrates exceptional academic and professional qualifications that make her a strong candidate for the Research for Best Researcher Award. Her education, spanning from a Bachelor’s to a Ph.D., reflects a consistent focus on biomedical physics with groundbreaking thesis work in non-invasive liver and cartilage evaluation using advanced imaging techniques. Her educational trajectory is complemented by prestigious scholarships, such as the Aktion Austria-Slovakia grant, showcasing her academic excellence.
Diana’s research output is prolific and impactful. She has authored high-quality journal articles and presented at prestigious international conferences, including the ISMRM and ESMRMB annual meetings. Her work on liver fibrosis classification using machine learning and texture analysis is particularly noteworthy, blending advanced imaging with computational approaches to address critical medical challenges. The breadth of her research, from liver MRI to cartilage imaging and brain spectroscopy, underscores her versatility and depth of expertise.
Education
Diana Sitarcikova’s academic journey is marked by excellence and a strong focus on biomedical physics. She is currently pursuing her PhD in Medical Physics at the Medical University of Vienna, where her research centers on multi-parametric non-invasive liver evaluation using advanced MRI techniques. She earned her Master’s degree in Biomedical Physics from Comenius University, Bratislava, with a thesis focused on non-invasive monitoring of the hepatobiliary system. During her Bachelor’s studies at the same institution, Diana explored phosphorus magnetic resonance spectroscopic imaging, comparing the quality of imaging at different field strengths and receiver configurations. Her academic achievements have been recognized through prestigious scholarships, including support from Aktion Austria-Slovakia. Diana’s educational background reflects her dedication to the integration of physics and medicine, equipping her with the skills to tackle complex challenges in biomedical imaging and diagnostics.
Professional Experience
Diana Sitarcikova’s professional experience is deeply rooted in cutting-edge research and development in biomedical imaging. As a PhD student at the Medical University of Vienna, she has conducted extensive research on liver and cartilage imaging, utilizing advanced techniques such as T1, T2, and T2* relaxometry, MR spectroscopy, and MR fingerprinting. Diana is proficient in texture and image analysis, employing methods like gray-level co-occurrence matrices and Gaussian-mixture models. Her work has contributed to the development of machine learning models for liver fibrosis classification and cartilage mapping. She has presented her findings at international conferences, including ISMRM and OARSI, gaining recognition for her innovative approaches. Diana’s expertise in Python, MATLAB, and R has been instrumental in data manipulation, visualization, and statistical analysis, enabling her to bridge the gap between technology and clinical applications. Her professional journey highlights her commitment to advancing medical imaging technologies.
Awards and Recognitions
Diana Sitarcikova has been the recipient of several awards and recognitions that underscore her academic and research excellence. In 2018, she received a prestigious scholarship from Aktion Austria-Slovakia, supporting her PhD studies at the Medical University of Vienna. Diana has co-authored numerous high-impact publications in leading journals, earning accolades for her innovative contributions to liver and cartilage imaging. She has actively participated in international conferences, such as ISMRM and OARSI, where her research on texture analysis and MR fingerprinting has been highly appreciated. Her ability to integrate machine learning techniques with medical imaging has positioned her as a rising star in the field. These achievements reflect Diana’s dedication to advancing diagnostic imaging and her potential to make significant contributions to radiology and biomedical physics.
Research Skills On Radiology
Diana Sitarcikova possesses a comprehensive set of research skills, particularly in the domain of medical imaging. Her expertise includes machine learning techniques such as classification models, feature engineering, and cluster analysis, which she applies to enhance diagnostic accuracy in liver fibrosis and cartilage evaluation. Diana is adept at texture analysis, using tools like gray-level co-occurrence matrices and local binary patterns to extract meaningful patterns from imaging data. Her image analysis capabilities encompass organ segmentation, volumetry, and Gaussian-mixture models for parameter extraction. Diana has extensive experience with advanced MRI techniques, including relaxometry, MR spectroscopy, and elastography for liver imaging, as well as MR fingerprinting for cartilage studies. Proficient in Python, MATLAB, and R, she excels in data visualization, statistical analysis, and image processing. Her interdisciplinary approach combines technical expertise and clinical insight, driving innovation in non-invasive diagnostic methods.
Publication Top Notes
1. Diagnostic accuracy of texture analysis applied to T1- and T2-Relaxation maps for liver fibrosis classification via machine-learning algorithms with liver histology as reference standard
- Authors: Diana Sitarcikova, Sarah Poetter-Lang, Nina Bastati, Sami Ba-Ssalamah, Siegfried Trattnig, Ulrike Attenberger, Ahmed Ba-Ssalamah, Martin Krššák
- Citation: European Journal of Radiology, DOI: 10.1016/j.ejrad.2024.111887
- Year: 2025
2. Evaluation of a single-breath-hold radial turbo-spin-echo sequence for T2 mapping of the liver at 3T
- Authors: Diana Sitarcikova, Diana Bencikova, Fei Han, Stephan Kannengieser, Marcus Raudner, Sarah Poetter-Lang, Nina Bastati, Gert Reiter, Raphael Ambros, Ahmed Ba-Ssalamah, et al.
- Citation: European Radiology, DOI: 10.1007/s00330-021-08439-y
- Year: 2022
3. Concentration of Gallbladder Phosphatidylcholine in Cholangiopathies: A Phosphorus‐31 Magnetic Resonance Spectroscopy Pilot Study
- Authors: Lorenz Pfleger, Emina Halilbasic, Martin Gajdošík, Diana Benčíková, Marek Chmelík, Thomas Scherer, Siegfried Trattnig, Michael Krebs, Michael Trauner, Martin Krššák
- Citation: Journal of Magnetic Resonance Imaging, DOI: 10.1002/jmri.27817
- Year: 2022