Erlend Hodneland

Erlend Hodneland is a Researcher at the University of Bergen's Department of Informatics, affiliated with the Mohn Medical Imaging and Visualization Centre (MMIV). His work bridges medical imaging, radiomics, and machine learning, focusing on tumor analysis and prognostication in cancers like cervical and endometrial cancers. He specializes in developing automated tumor segmentation techniques and tools for radiomic signature analysis, integrating visualization and computational methods to enhance clinical decision-making.

His research interests include medical imaging analytics, radiomics for cancer prognosis, and interactive visualization frameworks for multiparametric medical data. Collaborations involve radiologists, oncologists, and computer scientists to translate imaging data into actionable insights. Key projects include the RadEx platform for radiomic tumor profiling and automated segmentation algorithms for cervical cancer studies.

Notable contributions include MRI-based delta radiomics for tracking tumor responses during chemoradiotherapy and fully automatic whole-volume tumor segmentation. His work emphasizes precision medicine through quantitative imaging biomarkers and interdisciplinary approaches to medical data analysis.