News
Axti at the Paper Awards 2024!
Jessie Gommers did an excellent work and achieved third place at the paper awards 2024!! Congratulations Jessie!
AXTI Christmas Dinner
AXTI went out for Christmas Dinner in Nijmegen. See some photos here!
AXTI at RSNA!
AXTI is participating at RSNA in Chicago with the following exciting work:
Visitor: Zhikai Yang
Zhikai Yang is a PhD student at KTH Royal Institute of Technology, Division of Medical Imaging, Sweden. He is currently undertaking research on developing transparent AI for predicting the risk of developing breast cancer using radiological imaging. The main objective of this project is to develop and train transparent deep learning models for analyzing radiological data for diagnostic purposes in breast cancer and to recognize anatomic signs of predisposition for breast cancer. Specifically, he will mainly work with tomosynthesis (3D mammography) and 2D mammography images.
As an exchange student for three months in the AXTI lab, under the guidance of Daan van den Oever, Zhikai's aim is to gain valuable clinical experience and access breast radiological data.
MSc student: Davide Tuzzolino
Davide Tuzzolino started his thesis as a master student at the Politecnico di Torino, working on the development of a Deep Learning 2D DBT reconstruction algorithm using LEARN, in cooperation with Leonardo Coito Pereyra.
Visitor: Rigon Sallauka
Rigon Sallauka, a PhD student in Electrical Engineering at the University of Maribor, Slovenia, is currently undertaking research on developing an explainable and interpretable AI system to predict breast cancer recurrence. The research merges radiological, histopathological biomarkers, and clinical data for comprehensive analysis. As an exchange student for one month, under the guidance of Daan van den Oever, Rigon’s aim is to gain valuable clinical experience. His focus during the visit is to observe the day-to-day routines of radiologists involved in diagnosing primary breast cancer or recurrences, aiming to enrich his understanding of the clinical context surrounding his research.
MSc student: Lotte Kleimeier
Lotte Kleimeier is a Master's student in Biomedical Sciences at Radboud University. She conducted her master's thesis research at the AXTI lab, focusing on optimizing CT lymphangiography with insights into fluid dynamics. She collaborated with Liselot Goris and Luuk Oostveen. Her thesis highlighted challenges in achieving the desired opacification, underscoring the need for further research on lymphatic fluid properties. The findings suggest potential improvements in both diagnostic and therapeutic strategies for lymphatic imaging.
MSc student: Bas Willemsen
Bas Willemsen started his thesis as a master student from the University of Twente, focusing on the development of a deep learning algorithm to determine the risk of lesion masking in screening mammograms, working with Sarah Verboom.