1 code implementation • 10 Mar 2021 • Hans Liebl, David Schinz, Anjany Sekuboyina, Luca Malagutti, Maximilian T. Löffler, Amirhossein Bayat, Malek El Husseini, Giles Tetteh, Katharina Grau, Eva Niederreiter, Thomas Baum, Benedikt Wiestler, Bjoern Menze, Rickmer Braren, Claus Zimmer, Jan S. Kirschke
With the advent of deep learning algorithms, fully automated radiological image analysis is within reach.
no code implementations • 10 Mar 2021 • Florian Kofler, Ivan Ezhov, Fabian Isensee, Fabian Balsiger, Christoph Berger, Maximilian Koerner, Johannes Paetzold, Hongwei Li, Suprosanna Shit, Richard McKinley, Spyridon Bakas, Claus Zimmer, Donna Ankerst, Jan Kirschke, Benedikt Wiestler, Bjoern H. Menze
In this study, we explore quantitative correlates of qualitative human expert perception.
Our experiments show that, by replacing 3-D filters with cross-hair filters in our network, we achieve over 23% improvement in speed, lower memory footprint, lower network complexity which prevents overfitting and comparable accuracy (with a Cox-Wilcoxon paired sample significance test p-value of 0. 07 when compared to full 3-D filters).
Feature extraction is a very crucial task in image and pixel (voxel) classification and regression in biomedical image modeling.