BVM 2023

BVM Award CHILI

Anna-Maria Wölfl, Artificial Intelligence in Biomedical Engineering, FAU Erlangen-Nürnberg
"Pitch Detection in Endoscopic Images", Masterarbeit
Dr. Lasse Hansen, Institut für Medizinische Informatik, Universität zu Lübeck
"Point Clouds and Keypoint Graphs in 3D Deep Learning for Medical Image Analyssis", Doktorarbeit

Beste wissenschaftliche Arbeiten

Platz 1: Jonathan Ganz, Technische Hochschule Ingolstadt
Ganz J., Lipnik K., Ammeling J., Richter B., Puget C., Parlak E., Diehl L., Klopfleisch L., Donovan T. A., Kiupel M., Bertram C. A., Breininger K., Aubreville M.:
"Deep Learning-based Automatic Assessment of AgNOR-scores in Histopathology Images"
Platz 2: Marcel Ganß, Chair for Computer Aided Medical Procedures and Augmented Reality, Technical University Munich
Ganß M., De Benetti F., Brosch-Lenz J., Uribe-Munoz C., Shi K., Eiber M., Navab N., Wendler T.:
"Deep Learning Approaches for Contrast Removal from Contrast-enhanced CT"
Platz 3: Marc K. Ickler, Division of Medical Image Computing, German Cancer Research Center, Heidelberg
Ickler M. K., Baumgartner M., Roy S., Wald T., Maier-Hein K. H.:
"Taming Detection Transformers for Medical Object Detection"

Vortragspreis: Fabian Wagner, Pattern Recognition Lab, FAU Erlangen-Nürnberg

Wagner F., Thies M., Denzinger F., Gu M., Patwari M., Ploner S., Maul N., Pfaff L., Huang Y., Maier A.:
"Trainable Joint Bilateral Filters for Enhanced Prediction Stability in Low-dose CT"

Posterpreis: Robert Mendel, Regensburg Medical Image Computing (ReMIC), Ostbayerische Technische Hochschule Regensburg (OTH Regensburg)

Mendel R., Rauber D., Palm C.:
"Exploring the Effects of Contrastive Learning on Homogeneous Medical Image Data"

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