Based on the evaluation of the MLCN 2022 scientific committee on the scientific content, the significance of the contribution, and clarity of the communication, the MLCN2022 best paper award is presented to Margeritha Rosnati and her coauthors Eyal Soreq, Miguel Monteiro, Lucia Li, Neil S.N. Graham, Karl Zimmerman, Carlotta Rossi, Greta Carrara, Guido Bertolini, David Sharp, and Ben Glocker for the paper titled “Automatic Lesion Analysis for Increased Efficiency in Outcome Prediction of Traumatic Brain Injury”. The MLCN2022 best paper award is sponsored by Donders Institute for Brain, Cognition and Behaviour.
Margherita is a 3rd year Ph.D. student in the BioMedIA group at Imperial College, supervised by Ben Glocker and David Sharp. Her current work focuses on developing methods for data-efficient medical image segmentation, and she previously worked on improving the prediction of Traumatic Brain Injury outcomes for the affected patients. Before joining BioMedIA, Margherita obtained a master’s in Data Science at ETH Zurich and an undergraduate in Mathematics from Imperial College. Prior to entering academia, she spent a few years working as a trader for Goldman Sachs.
The winner is selected among 17 candidate papers. The runner-up papers for the best paper award are:
- Volume is All You Need: Improving Multi-task Multiple Instance Learning for WMH Segmentation and Severity Estimation. Wooseok Jung, Chong Hyun Suh, Woo Hyun Shim, Jinyoung Kim, Dongsoo Lee, Changhyun Park, Seo Taek Kong, Kyu-Hwan Jung, Hwon Heo, Sang Joon Kim.
- Concurrent ischemic lesion age estimation and segmentation of CT brain using a Transformer-based network. Adam Marcus, Paul Ben, Daniel Rueckert.
- fMRI-S4: learning short- and long-range dynamic fMRI dependencies using 1D Convolutions and State Space Models. Ahmed ElGazzar, Rajat Thomas, Guido Van Wingen.