Adaptive Affinity-Based Generalization For MRI Imaging Segmentation Across Resource-Limited Settings

arXiv:2404.02738v1 Announce Type: new
Abstract: The joint utilization of diverse data sources for medical imaging segmentation has emerged as a crucial area of research, aiming to address challenges such as data heterogeneity, domain shift, and data quality discrepancies. Integrating information from multiple data domains has shown promise in improving model generalizability and adaptability. However, this approach often demands substantial computational resources, hindering its practicality. In response, knowledge distillation (KD) has garnered attention as a solution. KD involves training light-weight models …

abstract arxiv challenges cs.cv data data quality data sources diverse domain domains imaging improving information medical medical imaging mri multiple quality research segmentation shift type