When Medical Imaging Met Self-Attention: A Love Story That Didn't Quite Work Out

arXiv:2404.12295v1 Announce Type: new
Abstract: A substantial body of research has focused on developing systems that assist medical professionals during labor-intensive early screening processes, many based on convolutional deep-learning architectures. Recently, multiple studies explored the application of so-called self-attention mechanisms in the vision domain. These studies often report empirical improvements over fully convolutional approaches on various datasets and tasks. To evaluate this trend for medical imaging, we extend two widely adopted convolutional architectures with different self-attention variants on two different …

abstract application architectures arxiv attention attention mechanisms cs.cv domain imaging labor love medical medical imaging multiple processes professionals research screening self-attention story studies systems type vision work