Automated Gleason Grading of Prostate Biopsies using Deep Learning

no code implementations • 18 Jul 2019 • Wouter Bulten, Hans Pinckaers, Hester van Boven, Robert Vink, Thomas de Bel, Bram van Ginneken, Jeroen van der Laak, Christina Hulsbergen-van de Kaa, Geert Litjens

We developed a fully automated deep learning system to grade prostate biopsies.

Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge

no code implementations • 23 Dec 2016 • Arnaud Arindra Adiyoso Setio, Alberto Traverso, Thomas de Bel, Moira S. N. Berens, Cas van den Bogaard, Piergiorgio Cerello, Hao Chen, Qi Dou, Maria Evelina Fantacci, Bram Geurts, Robbert van der Gugten, Pheng Ann Heng, Bart Jansen, Michael M. J. de Kaste, Valentin Kotov, Jack Yu-Hung Lin, Jeroen T. M. C. Manders, Alexander Sónora-Mengana, Juan Carlos García-Naranjo, Evgenia Papavasileiou, Mathias Prokop, Marco Saletta, Cornelia M Schaefer-Prokop, Ernst T. Scholten, Luuk Scholten, Miranda M. Snoeren, Ernesto Lopez Torres, Jef Vandemeulebroucke, Nicole Walasek, Guido C. A. Zuidhof, Bram van Ginneken, Colin Jacobs

We have therefore set up the LUNA16 challenge, an objective evaluation framework for automatic nodule detection algorithms using the largest publicly available reference database of chest CT scans, the LIDC-IDRI data set.

Computed Tomography (CT)