Rotational Invariance at Fixation Points - Experiments using Human Gaze Data. - Johannes Steffen; Christian Hentschel; Afra'a Ahmad Alyosef; Klaus D. Tönnies; Andreas Nürnberger (ICPRAM (2), 2012)

Texture-Based Detection of Myositis in Ultrasonographies. - Tim König; Marko Rak; Johannes Steffen; Grit Neumann; Ludwig von Rohden; Klaus D. Tönnies (Bildverarbeitung für die Medizin, 2013)

Density Difference Detection with Application to Exploratory Visualization. - Marko Rak; Tim König; Johannes Steffen; Dirk Joachim Lehmann; Klaus-Dietz Tönnies (ICPRAM (Selected Papers), 2015)

Ultrasound texture-based CAD system for detecting neuromuscular diseases. - Tim König; Johannes Steffen; Marko Rak; Grit Neumann; Ludwig von Rohden; Klaus D. Tönnies (Int. J. Comput. Assist. Radiol. Surg., 2015)

Information Efficient Automatic Object Detection and Segmentation using Cosegmentation, Similarity based Clustering, and Graph Label Transfer. - Johannes Steffen; Marko Rak; Tim König; Klaus-Dietz Tönnies (ICPRAM, 2016)

Perception Enhancement for Bionic Vision - Preliminary Study on Object Classification with Subretinal Implants. - Johannes Steffen; Jonathan Napp; Stefan Pollmann; Klaus Tönnies (ICPRAM, 2018)

Segmentation of Vertebral Metastases in MRI Using an U-Net like Convolutional Neural Network. - Georg Hille; Max Dünnwald; Mathias Becker; Johannes Steffen; Sylvia Saalfeld; Klaus Tönnies (Bildverarbeitung für die Medizin, 2019)

Automatic Perception Enhancement for Simulated Retinal Implants. - Johannes Steffen; Georg Hille; Klaus Tönnies (ICPRAM, 2019)

Combining convolutional neural networks and star convex cuts for fast whole spine vertebra segmentation in MRI. - Marko Rak; Johannes Steffen; Anneke Meyer; Christian Hansen 001; Klaus-Dietz Tönnies (Comput. Methods Programs Biomed., 2019)

Automatic Segmentation of Necrosis Zones after Radiofrequency Ablation of Spinal Metastases. - Johannes Steffen; Georg Hille; Mathias Becker; Sylvia Saalfeld; Klaus Tönnies (ICPRAM, 2020)

Spinal Metastases Segmentation in MR Imaging using Deep Convolutional Neural Networks. - Georg Hille; Johannes Steffen; Max Dünnwald; Mathias Becker; Sylvia Saalfeld; Klaus Tönnies (CoRR, 2020)