Erfolgreiches Lernen durch gamifiziertes E-Learning. - Friedrich Pawelka; Thomas Wollmann; Jakob Stöber; Tommy Vinh Lam (GI-Jahrestagung, 2014)

Formative Evaluation of Smartwatch Exergaming. - Nicola Marsden; Thomas Wollmann; Britta Lohmann; Gerrit Meixner (MuC (Workshopband), 2015)

User-Centred Design and Usability Evaluation of a Heart Rate Variability Biofeedback Game. - Thomas Wollmann; Farhad Abtahi; Aboozar Eghdam; Fernando Seoane; Kaj Lindecrantz; Martin Haag; Sabine Koch (IEEE Access, 2016)

Automatic Grading of Breast Cancer Whole-Slide Histopathology Images. - Thomas Wollmann; Karl Rohr (Bildverarbeitung für die Medizin, 2017)

Deep residual Hough voting for mitotic cell detection in histopathology images. - Thomas Wollmann; Karl Rohr (ISBI, 2017)

Automatic breast cancer grading in lymph nodes using a deep neural network. - Thomas Wollmann; Karl Rohr (CoRR, 2017)

Multi-channel Deep Transfer Learning for Nuclei Segmentation in Glioblastoma Cell Tissue Images. - Thomas Wollmann; Julia Ivanova; Manuel Gunkel; Inn Chung; Holger Erfle; Karsten Rippe; Karl Rohr (Bildverarbeitung für die Medizin, 2018)

Comparison of segmentation methods for tissue microscopy images of glioblastoma cells. - D. Baltissen; Thomas Wollmann; Manuel Gunkel; Inn Chung; Holger Erfle; Karsten Rippe; Karl Rohr (ISBI, 2018)

Adversarial domain adaptation to improve automatic breast cancer grading in lymph nodes. - Thomas Wollmann; C. S. Eijkman; Karl Rohr (ISBI, 2018)

Deep Particle Tracker: Automatic Tracking of Particles in Fluorescence Microscopy Images Using Deep Learning. - Roman Spilger; Thomas Wollmann; Yu Qiang; Andrea Imle; Ji Young Lee; Barbara Müller; Oliver T. Fackler; Ralf Bartenschlager; Karl Rohr (DLMIA/ML-CDS@MICCAI, 2018)

Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge. - Mitko Veta; Yujing J. Heng; Nikolas Stathonikos; Babak Ehteshami Bejnordi; Francisco Beca; Thomas Wollmann; Karl Rohr; Manan A. Shah; Dayong Wang; Mikaël Rousson; Martin Hedlund; David Tellez; et al. (CoRR, 2018)

Black-Box Hyperparameter Optimization for Nuclei Segmentation in Prostate Tissue Images. - Thomas Wollmann; Patrick Bernhard; Manuel Gunkel; Delia M. Braun; Jan Meiners; Ronald Simon; Guido Sauter; Holger Erfle; Karsten Rippe; Karl Rohr (Bildverarbeitung für die Medizin, 2019)

Detnet: Deep Neural Network For Particle Detection In Fluorescence Microscopy Images. - Thomas Wollmann; Christian Ritter; Jan-Niklas Dohrke; Ji Young Lee; Ralf Bartenschlager; Karl Rohr (ISBI, 2019)

Hyperparameter optimization for image analysis: application to prostate tissue images and live cell data of virus-infected cells. - Christian Ritter; Thomas Wollmann; Patrick Bernhard; Manuel Gunkel; Delia M. Braun; Ji Young Lee; Jan Meiners; Ronald Simon; Guido Sauter; Holger Erfle; Karsten Rippe; Ralf Bartenschlager; et al. (Int. J. Comput. Assist. Radiol. Surg., 2019)

Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge. - Mitko Veta; Yujing J. Heng; Nikolas Stathonikos; Babak Ehteshami Bejnordi; Francisco Beca; Thomas Wollmann; Karl Rohr; Manan A. Shah; Dayong Wang; Mikaël Rousson; Martin Hedlund; David Tellez; et al. (Medical Image Anal., 2019)

GRUU-Net: Integrated convolutional and gated recurrent neural network for cell segmentation. - Thomas Wollmann; Manuel Gunkel; Inn Chung; Holger Erfle; Karsten Rippe; Karl Rohr (Medical Image Anal., 2019)

Deep Learning Particle Detection for Probabilistic Tracking in Fluorescence Microscopy Images. - Christian Ritter; Thomas Wollmann; Ji Young Lee; Ralf Bartenschlager; Karl Rohr (ISBI, 2020)

Chameleon: A Semi-AutoML framework targeting quick and scalable development and deployment of production-ready ML systems for SMEs. - Johannes S. Otterbach; Thomas Wollmann (GI-Jahrestagung, 2021)

MEAL: Manifold Embedding-based Active Learning. - Deepthi Sreenivasaiah; Johannes S. Otterbach; Thomas Wollmann (ICCVW, 2021)

DAAIN: Detection of Anomalous and Adversarial Input using Normalizing Flows. - Samuel von Baußnern; Johannes S. Otterbach; Adrian Loy; Mathieu Salzmann; Thomas Wollmann (CoRR, 2021)

MEAL: Manifold Embedding-based Active Learning. - Deepthi Sreenivasaiah; Thomas Wollmann (CoRR, 2021)

Data fusion and smoothing for probabilistic tracking of viral structures in fluorescence microscopy images. - Christian Ritter; Thomas Wollmann; Ji Young Lee; Andrea Imle; Barbara Müller; Oliver T. Fackler; Ralf Bartenschlager; Karl Rohr (Medical Image Anal., 2021)

Deep Consensus Network: Aggregating predictions to improve object detection in microscopy images. - Thomas Wollmann; Karl Rohr (Medical Image Anal., 2021)

Galaxy Training: A powerful framework for teaching! - Saskia D. Hiltemann; Helena Rasche; Simon L. Gladman; Hans-Rudolf Hotz; Delphine Larivière; Daniel J. Blankenberg; Pratik D. Jagtap; Thomas Wollmann; Anthony Bretaudeau; Nadia Goué; Timothy J. Griffin; Coline Royaux; et al. (PLoS Comput. Biol., 2023)

Choose Your Model Size: Any Compression by a Single Gradient Descent. - Martin Genzel; Patrick Putzky; Pengfei Zhao; Sebastian Schulze; Mattes Mollenhauer; Robert Seidel; Stefan Dietzel; Thomas Wollmann (CoRR, 2025)