Crop and Couple: cardiac image segmentation using interlinked specialist
  networks
Abbas Khan Muhammad Asad Martin Benning Caroline Roney Gregory Slabaugh
Diagnosis of cardiovascular disease using automated methods often relies on
the critical task of cardiac image segmentation. We propose a novel strategy
that performs segmentation using specialist networks that focus on a single
anatomy (left ventricle, right ventricle, or myocardium). Given an input
long-axis cardiac MR image, our method performs a ternary segmentation in the
first stage to identify these anatomical regions, followed by cropping the
original image to focus subsequent processing on the anatomical regions. The
specialist networks are coupled through an attention mechanism that performs
cross-attention to interlink features from different anatomies, serving as a
soft relative shape prior. Central to our approach is an additive attention
block (E-2A block), which is used throughout our architecture thanks to its
efficiency.