CNNs as Inverse Problem Solvers and Double Network Superresolution

no code implementations • ICLR 2018 • Cem Tarhan, Gözde BOZDAĞI AKAR

In recent years Convolutional Neural Networks (CNN) have been used extensively for Superresolution (SR).

CHAOS Challenge -- Combined (CT-MR) Healthy Abdominal Organ Segmentation

1 code implementation • 17 Jan 2020 • A. Emre Kavur, N. Sinem Gezer, Mustafa Barış, Sinem Aslan, Pierre-Henri Conze, Vladimir Groza, Duc Duy Pham, Soumick Chatterjee, Philipp Ernst, Savaş Özkan, Bora Baydar, Dmitry Lachinov, Shuo Han, Josef Pauli, Fabian Isensee, Matthias Perkonigg, Rachana Sathish, Ronnie Rajan, Debdoot Sheet, Gurbandurdy Dovletov, Oliver Speck, Andreas Nürnberger, Klaus H. Maier-Hein, Gözde BOZDAĞI AKAR, Gözde Ünal, Oğuz Dicle, M. Alper Selver

The analysis shows that the performance of DL models for single modality (CT / MR) can show reliable volumetric analysis performance (DICE: 0. 98 $\pm$ 0. 00 / 0. 95 $\pm$ 0. 01) but the best MSSD performance remain limited (21. 89 $\pm$ 13. 94 / 20. 85 $\pm$ 10. 63 mm).

Organ Segmentation Segmentation