CVPR 2023 – Neuralizer: General Neuroimage Analysis without Re-Training

In this episode we discuss Neuralizer: General Neuroimage Analysis without Re-Training
by Steffen Czolbe, Adrian V. Dalca. The paper discusses the challenges in using deep learning for neuroimage processing tasks such as segmentation and registration. The authors introduce a new model called Neuralizer that can generalize to previously unseen tasks and modalities without the need for re-training or fine-tuning. The model can solve processing tasks across multiple image modalities and datasets, and outperforms task-specific baselines even when few annotated subjects are available. The goal is to provide a tool that can be adopted by neuroscientists and clinical researchers who may lack the resources or expertise to train deep learning models.