`Project & Excite' Modules for Segmentation of Volumetric Medical Scans

11 Jun 2019Anne-Marie RickmannAbhijit Guha RoyIgnacio SarasuaNassir NavabChristian Wachinger

Fully Convolutional Neural Networks (F-CNNs) achieve state-of-the-art performance for image segmentation in medical imaging. Recently, squeeze and excitation (SE) modules and variations thereof have been introduced to recalibrate feature maps channel- and spatial-wise, which can boost performance while only minimally increasing model complexity... (read more)

PDF Abstract

Evaluation results from the paper


  Submit results from this paper to get state-of-the-art GitHub badges and help community compare results to other papers.