Image Segmentation of Vickers Indentations Using Shape from Focus. - Michael Gadermayr; Andreas Uhl (ICIAR (1), 2012)

Dual-Resolution Active Contours Segmentation of Vickers Indentation Images with Shape Prior Initialization. - Michael Gadermayr; Andreas Uhl (ICISP, 2012)

The Impact of Unfocused Vickers Indentation Images on the Segmentation Performance. - Michael Gadermayr; Andreas Maier 004; Andreas Uhl (ISVC (2), 2012)

Robust algorithm for automated microindentation measurement in Vickers hardness testing. - Michael Gadermayr; Andreas Maier 004; Andreas Uhl (J. Electronic Imaging, 2012)

Problems in Distortion Corrected Texture Classification and the Impact of Scale and Interpolation. - Michael Gadermayr; Michael Liedlgruber; Andreas Uhl; Andreas Vécsei (ICIAP (1), 2013)

Barrel-Type Distortion Compensated Fourier Feature Extraction. - Michael Gadermayr; Andreas Uhl; Andreas Vécsei (ISVC (1), 2013)

Distortion Adaptive Image Classification - An Alternative to Barrel-Type Distortion Correction. - Michael Gadermayr; Andreas Uhl; Andreas Vécsei (ISVC (2), 2013)

Shape Curvature Histogram: A Shape Feature for Celiac Disease Diagnosis. - Michael Gadermayr; Michael Liedlgruber; Andreas Uhl; Andreas Vécsei (MCV, 2013)

Feature Extraction with Intrinsic Distortion Correction in Celiac Disease Imagery: No Need for Rasterization. - Michael Gadermayr; Andreas Uhl; Andreas Vécsei (MCV, 2013)

Evaluation of different distortion correction methods and interpolation techniques for an automated classification of celiac disease. - Michael Gadermayr; Michael Liedlgruber; Andreas Uhl; Andreas Vécsei (Comput. Methods Programs Biomed., 2013)

Active contours methods with respect to Vickers indentations. - Michael Gadermayr; Andreas Maier 004; Andreas Uhl (Mach. Vis. Appl., 2013)

The Effect of Endoscopic Lens Distortion Correction on Physicians' Diagnosis Performance. - Michael Gadermayr; Andreas Uhl; Andreas Vécsei (Bildverarbeitung für die Medizin, 2014)

Quality Based Information Fusion in Fully Automatized Celiac Disease Diagnosis. - Michael Gadermayr; Andreas Uhl; Andreas Vécsei (GCPR, 2014)

Degradation Adaptive Texture Classification: A Case Study in Celiac Disease Diagnosis Brings New Insight. - Michael Gadermayr; Andreas Uhl; Andreas Vécsei (ICIAR (2), 2014)

Degradation adaptive texture classification. - Michael Gadermayr; Andreas Uhl (ICIP, 2014)

Is a Precise Distortion Estimation Needed for Computer Aided Celiac Disease Diagnosis? - Michael Gadermayr; Andreas Uhl; Andreas Vécsei (ICISP, 2014)

Scale-Adaptive Texture Classification. - Michael Gadermayr; Sebastian Hegenbart; Andreas Uhl (ICPR, 2014)

Getting one step closer to fully automatized celiac disease diagnosis. - Michael Gadermayr; Andreas Uhl; Andreas Vécsei (IPTA, 2014)

Dealing with Intra-Class and Intra-Image Variations in Automatic Celiac Disease Diagnosis. - Michael Gadermayr; Andreas Uhl; Andreas Vécsei (Bildverarbeitung für die Medizin, 2015)

How to exploit large image data in the fields of texture classification: A case study with local binary patterns. - Michael Gadermayr; Andreas Uhl (ICIP, 2015)

Comparing endoscopic imaging configurations in computer-aided celiac disease diagnosis. - Michael Gadermayr; Hubert Kogler; Andreas Uhl; Andreas Vécsei (IPTA, 2015)

Boosting Small-Data Performance of LBP: A Case Study in Celiac Disease Diagnosis. - Michael Gadermayr; Andreas Uhl; Andreas Vécsei (SCIA, 2015)

Domain Adaptive Classification for Compensating Variability in Histopathological Whole Slide Images. - Michael Gadermayr; Martin Strauch; Barbara Mara Klinkhammer; Sonja Djudjaj; Peter Boor; Dorit Merhof (ICIAR, 2016)

Incorporating human knowledge in automated celiac disease diagnosis. - Michael Gadermayr; Hubert Kogler; Maximilian Karla; Andreas Vécsei; Andreas Uhl; Dorit Merhof (IPTA, 2016)

Narrow band imaging versus white-light: What is best for computer-assisted diagnosis of celiac disease? - Michael Gadermayr; Sebastian Hegenbart; Roland Kwitt; Andreas Uhl; Andreas Vécsei (ISBI, 2016)

Do We Need Large Annotated Training Data for Detection Applications in Biomedical Imaging? A Case Study in Renal Glomeruli Detection. - Michael Gadermayr; Barbara Mara Klinkhammer; Peter Boor; Dorit Merhof (MLMI@MICCAI, 2016)

Evaluation of i-Scan Virtual Chromoendoscopy and Traditional Chromoendoscopy for the Automated Diagnosis of Colonic Polyps. - Georg Wimmer; Michael Gadermayr; Roland Kwitt; Michael Häfner; Dorit Merhof; Andreas Uhl (CARE@MICCAI, 2016)

A Feasibility Study on Automated Protein Aggregate Characterization Utilizing a Hybrid Classification Model. - Dennis Eschweiler; Michael Gadermayr; Jakob Unger; Markus Nippold; Björn Falkenburger; Dorit Merhof (VCBM/MedViz, 2016)

Making texture descriptors invariant to blur. - Michael Gadermayr; Andreas Uhl (EURASIP J. Image Video Process., 2016)

A Quantitative Assessment of Image Normalization for Classifying Histopathological Tissue of the Kidney. - Michael Gadermayr; Sean Steven Cooper; Barbara Mara Klinkhammer; Peter Boor; Dorit Merhof (GCPR, 2017)

Fully-Automated CNN-Based Computer Aided Celiac Disease Diagnosis. - Michael Gadermayr; Georg Wimmer; Andreas Uhl; Hubert Kogler; Andreas Vécsei; Dorit Merhof (ICIAP (2), 2017)

Segmenting renal whole slide images virtually without training data. - Michael Gadermayr; Dennis Eschweiler; Abiramjee Jeevanesan; Barbara Mara Klinkhammer; Peter Boor; Dorit Merhof (Comput. Biol. Medicine, 2017)

CNN Cascades for Segmenting Whole Slide Images of the Kidney. - Michael Gadermayr; Ann-Kathrin Dombrowski; Barbara Mara Klinkhammer; Peter Boor; Dorit Merhof (CoRR, 2017)

Gradual Domain Adaptation for Segmenting Whole Slide Images Showing Pathological Variability. - Michael Gadermayr; Dennis Eschweiler; Barbara Mara Klinkhammer; Peter Boor; Dorit Merhof (ICISP, 2018)

Stain independent segmentation of whole slide images: A case study in renal histology. - Laxmi Gupta; Barbara Mara Klinkhammer; Peter Boor; Dorit Merhof; Michael Gadermayr (ISBI, 2018)

Which Way Round? A Study on the Performance of Stain-Translation for Segmenting Arbitrarily Dyed Histological Images. - Michael Gadermayr; Vitus Appel; Barbara Mara Klinkhammer; Peter Boor; Dorit Merhof (MICCAI (2), 2018)

Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis. - Michael Gadermayr; Georg Wimmer; Hubert Kogler; Andreas Vécsei; Dorit Merhof; Andreas Uhl (Comput. Biol. Medicine, 2018)

Training of polyp staging systems using mixed imaging modalities. - Georg Wimmer; Michael Gadermayr; Roland Kwitt; Michael Häfner; Toru Tamaki; Shigeto Yoshida; Shinji Tanaka; Dorit Merhof; Andreas Uhl (Comput. Biol. Medicine, 2018)

Virtually Redying Histological Images with Generative Adversarial Networks to Facilitate Unsupervised Segmentation: A Proof-of-Concept Study. - Michael Gadermayr; Barbara Mara Klinkhammer; Peter Boor (ECDP, 2019)

GAN-Based Image Enrichment in Digital Pathology Boosts Segmentation Accuracy. - Laxmi Gupta; Barbara Mara Klinkhammer; Peter Boor; Dorit Merhof; Michael Gadermayr (MICCAI (1), 2019)

Unsupervisedly Training GANs for Segmenting Digital Pathology with Automatically Generated Annotations. - Michael Gadermayr; Laxmi Gupta; Barbara Mara Klinkhammer; Peter Boor; Dorit Merhof (MIDL, 2019)

Iterative learning to make the most of unlabeled and quickly obtained labeled data in histology. - Laxmi Gupta; Barbara Mara Klinkhammer; Peter Boor; Dorit Merhof; Michael Gadermayr (MIDL, 2019)

CNN cascades for segmenting sparse objects in gigapixel whole slide images. - Michael Gadermayr; Ann-Kathrin Dombrowski; Barbara Mara Klinkhammer; Peter Boor; Dorit Merhof (Comput. Medical Imaging Graph., 2019)

Generative Adversarial Networks for Facilitating Stain-Independent Supervised and Unsupervised Segmentation: A Study on Kidney Histology. - Michael Gadermayr; Laxmi Gupta; Vitus Appel; Peter Boor; Barbara Mara Klinkhammer; Dorit Merhof (IEEE Trans. Medical Imaging, 2019)

Improving Endoscopic Decision Support Systems by Translating Between Imaging Modalities. - Georg Wimmer; Michael Gadermayr; Andreas Vécsei; Andreas Uhl (SASHIMI@MICCAI, 2020)

An Asymetric Cycle-Consistency Loss for Dealing with Many-to-One Mappings in Image Translation: A Study on Thigh MR Scans. - Michael Gadermayr; Maximilian Ernst Tschuchnig; Dorit Merhof; Nils Krämer; Daniel Truhn; Burkhard Gess (CoRR, 2020)

Generative Adversarial Networks in Digital Pathology: A Survey on Trends and Future Potential. - Maximilian Ernst Tschuchnig; Gertie Janneke Oostingh; Michael Gadermayr (Patterns, 2020)

An Asymmetric Cycle-Consistency Loss For Dealing With Many-To-One Mappings In Image Translation: A Study On Thigh Mr Scans. - Michael Gadermayr; Maximilian Ernst Tschuchnig; Laxmi Gupta; Nils Krämer; Daniel Truhn; Dorit Merhof; Burkhard Gess (ISBI, 2021)

Frozen-to-Paraffin: Categorization of Histological Frozen Sections by the Aid of Paraffin Sections and Generative Adversarial Networks. - Michael Gadermayr; Maximilian Ernst Tschuchnig; Lea Maria Stangassinger; Christina Kreutzer; Sebastien Couillard-Despres; Gertie Janneke Oostingh; Anton Hittmair (SASHIMI@MICCAI, 2021)

Quantification of anomalies in rats' spinal cords using autoencoders. - Maximilian Ernst Tschuchnig; Dominic Zillner; Pasquale Romanelli; David Hercher; Patrick Heimel; Gertie Janneke Oostingh; Sebastien Couillard-Despres; Michael Gadermayr (Comput. Biol. Medicine, 2021)

Anomaly Detection in Medical Imaging - A Mini Review. - Maximilian Ernst Tschuchnig; Michael Gadermayr (CoRR, 2021)

Beyond Desktop Computation: Challenges in Scaling a GPU Infrastructure. - Martin Uray; Eduard Hirsch; Gerold Katzinger; Michael Gadermayr (CoRR, 2021)

Evaluation of Multi-Scale Multiple Instance Learning to Improve Thyroid Cancer Classification. - Maximilian Ernst Tschuchnig; Philipp Grubmüller; Lea Maria Stangassinger; Christina Kreutzer; Sebastien Couillard-Despres; Gertie Janneke Oostingh; Anton Hittmair; Michael Gadermayr (IPTA, 2022)

Automated major psoas muscle volumetry in computed tomography using machine learning algorithms. - Felix Duong; Michael Gadermayr; Dorit Merhof; Christiane Kuhl; Philipp Bruners; Sven H. Loosen; Christoph Roderburg; Daniel Truhn; Maximilian F. Schulze-Hagen (Int. J. Comput. Assist. Radiol. Surg., 2022)

MixUp-MIL: Novel Data Augmentation for Multiple Instance Learning and a Study on Thyroid Cancer Diagnosis. - Michael Gadermayr; Lukas Koller; Maximilian Ernst Tschuchnig; Lea Maria Stangassinger; Christina Kreutzer; Sebastien Couillard-Despres; Gertie Janneke Oostingh; Anton Hittmair (MICCAI (6), 2023)

MixUp-MIL: A Study on Linear & Multilinear Interpolation-Based Data Augmentation for Whole Slide Image Classification. - Michael Gadermayr; Lukas Koller; Maximilian Ernst Tschuchnig; Lea Maria Stangassinger; Christina Kreutzer; Sebastien Couillard-Despres; Gertie Janneke Oostingh; Anton Hittmair (CoRR, 2023)

Multi-task Learning to Improve Semantic Segmentation of CBCT Scans using Image Reconstruction. - Maximilian Ernst Tschuchnig; Julia Coste-Marin; Philipp Steininger; Michael Gadermayr (Bildverarbeitung für die Medizin, 2024)

Virtually Objective Quantification of in vitro Wound Healing Scratch Assays with the Segment Anything Model. - Katja Löwenstein; Johanna Rehrl; Anja Schuster; Michael Gadermayr (VCBM, 2024)

CBCTLiTS: A Synthetic, Paired CBCT/CT Dataset For Segmentation And Style Transfer. - Maximilian Ernst Tschuchnig; Philipp Steininger; Michael Gadermayr (VCBM, 2024)

Multiple instance learning for digital pathology: A review of the state-of-the-art, limitations & future potential. - Michael Gadermayr; Maximilian Ernst Tschuchnig (Comput. Medical Imaging Graph., 2024)

Multimodal Learning With Intraoperative CBCT & Variably Aligned Preoperative CT Data To Improve Segmentation. - Maximilian Ernst Tschuchnig; Philipp Steininger; Michael Gadermayr (CoRR, 2024)

Initial Study On Improving Segmentation By Combining Preoperative CT And Intraoperative CBCT Using Synthetic Data. - Maximilian Ernst Tschuchnig; Philipp Steininger; Michael Gadermayr (CoRR, 2024)

Improving Segmentation by Combining Preoperative CT and Intraoperative CBCT using Synthetic Data. - Maximilian Ernst Tschuchnig; Philipp Steininger; Michael Gadermayr (Bildverarbeitung für die Medizin, 2025)

Enhancing Synthetic CT from CBCT via Multimodal Fusion: A Study on the Impact of CBCT Quality and Alignment. - Maximilian Ernst Tschuchnig; Lukas Lamminger; Philipp Steininger; Michael Gadermayr (CoRR, 2025)

Enhancing Synthetic CT from CBCT via Multimodal Fusion and End-To-End Registration. - Maximilian Ernst Tschuchnig; Lukas Lamminger; Philipp Steininger; Michael Gadermayr (CoRR, 2025)

Hybrid Deep Learning and Handcrafted Feature Fusion for Mammographic Breast Cancer Classification. - Maximilian Ernst Tschuchnig; Michael Gadermayr; Khalifa Djemal (CoRR, 2025)