Computational TMA Analysis and Cell Nucleus Classification of Renal Cell Carcinoma. - Peter J. Schüffler; Thomas J. Fuchs; Cheng Soon Ong; Volker Roth 001; Joachim M. Buhmann (DAGM-Symposium, 2010)

A Multiple Kernel Learning Algorithm for Cell Nucleus Classification of Renal Cell Carcinoma. - Peter J. Schüffler; Aydin Ulas; Umberto Castellani; Vittorio Murino (ICIAP (1), 2011)

Renal Cancer Cell Classification Using Generative Embeddings and Information Theoretic Kernels. - Manuele Bicego; Aydin Ulas; Peter J. Schüffler; Umberto Castellani; Vittorio Murino; André F. T. Martins; Pedro M. Q. Aguiar; Mário A. T. Figueiredo (PRIB, 2011)

Combining Data Sources Nonlinearly for Cell Nucleus Classification of Renal Cell Carcinoma. - Mehmet Gönen; Aydin Ulas; Peter J. Schüffler; Umberto Castellani; Vittorio Murino (SIMBAD, 2011)

Hybrid Generative-Discriminative Nucleus Classification of Renal Cell Carcinoma. - Aydin Ulas; Peter J. Schüffler; Manuele Bicego; Umberto Castellani; Vittorio Murino (SIMBAD, 2011)

Computational modeling for assessment of IBD: To be or not to be? - Franciscus M. Vos; Jeroen A. W. Tielbeek; Robiel E. Naziroglu; Zhang Li; Peter Schueffler; Dwarikanath Mahapatra; Alexander Wiebel; Cristina Lavini; Joachim M. Buhmann; Hans-Christian Hege; Jaap Stoker; Lucas J. van Vliet (EMBC, 2012)

A Supervised Learning Based Approach to Detect Crohn's Disease in Abdominal MR Volumes. - Dwarikanath Mahapatra; Peter Schueffler; Jeroen A. W. Tielbeek; Joachim M. Buhmann; Franciscus M. Vos (Abdominal Imaging, 2012)

Crohn's disease tissue segmentation from abdominal MRI using semantic information and graph cuts. - Dwarikanath Mahapatra; Peter J. Schüffler; Jeroen A. W. Tielbeek; Franciscus M. Vos; Joachim M. Buhmann (ISBI, 2013)

Weakly supervised semantic segmentation of Crohn's disease tissues from abdominal MRI. - Dwarikanath Mahapatra; Alexander Vezhnevets; Peter J. Schüffler; Jeroen A. W. Tielbeek; Franciscus M. Vos; Joachim M. Buhmann (ISBI, 2013)

Semi-Supervised and Active Learning for Automatic Segmentation of Crohn's Disease. - Dwarikanath Mahapatra; Peter J. Schüffler; Jeroen A. W. Tielbeek; Franciscus M. Vos; Joachim M. Buhmann (MICCAI (2), 2013)

A Model Development Pipeline for Crohn's Disease Severity Assessment from Magnetic Resonance Images. - Peter J. Schüffler; Dwarikanath Mahapatra; Jeroen A. W. Tielbeek; Franciscus M. Vos; Jesica Makanyanga; Doug Pendsé; C. Yung Nio; Jaap Stoker; Stuart A. Taylor; Joachim M. Buhmann (Abdominal Imaging, 2013)

Localizing and segmenting Crohn's disease affected regions in abdominal MRI using novel context features. - Dwarikanath Mahapatra; Peter J. Schüffler; Jeroen A. W. Tielbeek; Franciscus M. Vos; Joachim M. Buhmann (Image Processing, 2013)

A Supervised Learning Approach for Crohn's Disease Detection Using Higher-Order Image Statistics and a Novel Shape Asymmetry Measure. - Dwarikanath Mahapatra; Peter Schueffler; Jeroen A. W. Tielbeek; Joachim M. Buhmann; Franciscus M. Vos (J. Digit. Imaging, 2013)

Automatic Detection and Segmentation of Crohn's Disease Tissues From Abdominal MRI. - Dwarikanath Mahapatra; Peter J. Schüffler; Jeroen A. W. Tielbeek; Jesica Makanyanga; Jaap Stoker; Stuart A. Taylor; Franciscus M. Vos; Joachim M. Buhmann (IEEE Trans. Medical Imaging, 2013)

Automated Analysis of Tissue Micro-Array Images on the Example of Renal Cell Carcinoma. - Peter J. Schüffler; Thomas J. Fuchs; Cheng Soon Ong; Volker Roth 001; Joachim M. Buhmann (Similarity-Based Pattern Analysis and Recognition, 2013)

Active learning based segmentation of Crohn's disease using principles of visual saliency. - Dwarikanath Mahapatra; Peter J. Schüffler; Jeroen A. W. Tielbeek; Jesica Makanyanga; Jaap Stoker; Stuart A. Taylor; Franciscus M. Vos; Joachim M. Buhmann (ISBI, 2014)

Combining Multiple Expert Annotations Using Semi-supervised Learning and Graph Cuts for Crohn's Disease Segmentation. - Dwarikanath Mahapatra; Peter J. Schüffler; Jeroen A. W. Tielbeek; Carl A. J. Puylaert; Jesica C. Makanyanga; Alex Menys; Rado Andriantsimiavona; Jaap Stoker; Stuart A. Taylor; Franciscus M. Vos; Joachim M. Buhmann (ABDI@MICCAI, 2014)

Semi-automatic Crohn's Disease Severity Estimation on MR Imaging. - Peter J. Schüffler; Dwarikanath Mahapatra; Robiel Naziroglu; Zhang Li; Carl A. J. Puylaert; Rado Andriantsimiavona; Franciscus M. Vos; Doug A. Pendsé; C. Yung Nio; Jaap Stoker; Stuart A. Taylor; Joachim M. Buhmann (ABDI@MICCAI, 2014)

Crohn's disease segmentation from MRI using learned image priors. - Dwarikanath Mahapatra; Peter J. Schüffler; Frans Vos; Joachim M. Buhmann (ISBI, 2015)

DeepScope: Nonintrusive Whole Slide Saliency Annotation and Prediction from Pathologists at the Microscope. - Andrew J. Schaumberg; S. Joseph Sirintrapun; Hikmat A. Al-Ahmadie; Peter J. Schüffler; Thomas J. Fuchs (CIBB, 2016)

Mitochondria-based Renal Cell Carcinoma Subtyping: Learning from Deep vs. Flat Feature Representations. - Peter J. Schüffler; Judy Sarungbam; Hassan Muhammad; Ed Reznik; Satish K. Tickoo; Thomas J. Fuchs (MLHC, 2016)

Multi-Organ Cancer Classification and Survival Analysis. - Stefan Bauer; Nicolas Carion; Peter J. Schüffler; Thomas J. Fuchs; Peter J. Wild; Joachim M. Buhmann (CoRR, 2016)

MRI-Based Surgical Planning for Lumbar Spinal Stenosis. - Gabriele Abbati; Stefan Bauer; Sebastian Winklhofer; Peter J. Schüffler; Ulrike Held; Jakob M. Burgstaller; Johann Steurer; Joachim M. Buhmann (MICCAI (3), 2017)

Towards machine learned quality control: A benchmark for sharpness quantification in digital pathology. - Gabriele Campanella; Arjun R. Rajanna; Lorraine Corsale; Peter J. Schüffler; Yukako Yagi; Thomas J. Fuchs (Comput. Medical Imaging Graph., 2018)

Deep Interactive Learning: An Efficient Labeling Approach for Deep Learning-Based Osteosarcoma Treatment Response Assessment. - David Joon Ho; Narasimhan P. Agaram; Peter J. Schüffler; Chad M. Vanderbilt; Marc-Henri Jean; Meera R. Hameed; Thomas J. Fuchs (MICCAI (5), 2020)

Deep Learning Methods for Lung Cancer Segmentation in Whole-slide Histopathology Images - the ACDC@LungHP Challenge 2019. - Zhang Li; Jiehua Zhang; Tao Tan 002; Xichao Teng; Xiaoliang Sun; Yang Li 058; Lihong Liu; Yang Xiao; Byungjae Lee; Yilong Li; Qianni Zhang; Shujiao Sun; et al. (CoRR, 2020)

Quantifying Heterogeneity in Tumors: Proposing a New Method Utilizing Convolutional Neuronal Networks. - Georg Prokop; Michael Örtl; Marina Fotteler; Peter J. Schüffler; Johannes Schobel; Walter Swoboda; Jürgen Schlegel; Friederike Liesche-Starnecker (ICIMTH, 2021)

Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center. - Peter J. Schüffler; Luke Geneslaw; Dig Vijay Kumar Yarlagadda; Matthew G. Hanna; Jennifer Samboy; Evangelos Stamelos; Chad M. Vanderbilt; John Philip; Marc-Henri Jean; Lorraine Corsale; Allyne Manzo; Neeraj H. G. Paramasivam; et al. (J. Am. Medical Informatics Assoc., 2021)

Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images - The ACDC@LungHP Challenge 2019. - Zhang Li; Jiehua Zhang; Tao Tan 002; Xichao Teng; Xiaoliang Sun; Hong Zhao; Lihong Liu; Yang Xiao; Byungjae Lee; Yilong Li; Qianni Zhang; Shujiao Sun; et al. (IEEE J. Biomed. Health Informatics, 2021)

DICOM Whole Slide Imaging for Computational Pathology Research in Kaapana and the Joint Imaging Platform. - Maximilian Fischer; Philipp Schader; Rickmer Braren; Michael Götz; Alexander Muckenhuber; Wilko Weichert; Peter J. Schüffler; Jens Kleesiek; Jonas Scherer; Klaus Kades; Klaus H. Maier-Hein; Marco Nolden (Bildverarbeitung für die Medizin, 2022)

Deep Learning on Lossily Compressed Pathology Images: Adverse Effects for ImageNet Pre-trained Models. - Maximilian Fischer; Peter Neher; Michael Götz; Shuhan Xiao; Silvia Dias Almeida; Peter J. Schüffler; Alexander Muckenhuber; Rickmer Braren; Jens Kleesiek; Marco Nolden; Klaus H. Maier-Hein (MOVI@MICCAI, 2022)

Abstract: Deep-learning on Lossily Compressed Pathology Images - Adverse Effects for ImageNet Pre-trained Models. - Maximilian Fischer; Peter Neher; Michael Götz; Shuhan Xiao; Silvia Dias Almeida; Peter J. Schüffler; Alexander Muckenhuber; Rickmer Braren; Jens Kleesiek; Marco Nolden; Klaus H. Maier-Hein (Bildverarbeitung für die Medizin, 2023)

Multimodal Context-Aware Detection of Glioma Biomarkers Using MRI and WSI. - Tomé Albuquerque; Mei Ling Fang; Benedikt Wiestler; Claire Delbridge; Maria João M. Vasconcelos; Jaime S. Cardoso 001; Peter J. Schüffler (MTSAIL/LEAF/AI4Treat/MMMI/REMIA@MICCAI, 2023)

DISBELIEVE: Distance Between Client Models Is Very Essential for Effective Local Model Poisoning Attacks. - Indu Joshi; Priyank Upadhya; Gaurav Kumar Nayak; Peter J. Schüffler; Nassir Navab (ISIC/Care-AI/MedAGI/DeCaF@MICCAI, 2023)

Whole Slide Multiple Instance Learning for Predicting Axillary Lymph Node Metastasis. - Glejdis Shkëmbi; Johanna P. Müller; Zhe Li 025; Katharina Breininger; Peter J. Schüffler; Bernhard Kainz (DEMI@MICCAI, 2023)

Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning. - Maximilian Fischer; Peter Neher; Peter J. Schüffler; Shuhan Xiao; Silvia Dias Almeida; Constantin Ulrich; Alexander Muckenhuber; Rickmer Braren; Michael Götz; Jens Kleesiek; Marco Nolden; Klaus H. Maier-Hein (MLMI@MICCAI (2), 2023)

Pan-Tumor T-Lymphocyte Detection Dataset. - Frauke Wilm; Christian Ihling; Gabor Mehes; Luigi Terracciano; Chloé Puget; Robert Klopfleisch; Peter J. Schüffler; Marc Aubreville; Andreas Maier 001; Thomas Mrowiec; Katharina Breininger (Zenodo, 2023)

Abstract: Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning. - Maximilian Fischer; Peter Neher; Peter J. Schüffler; Shuhan Xiao; Silvia Dias Almeida; Constantin Ulrich; Alexander Muckenhuber; Rickmer Braren; Michael Götz; Jens Kleesiek; Marco Nolden; Klaus H. Maier-Hein (Bildverarbeitung für die Medizin, 2024)

Learned Image Compression for HE-Stained Histopathological Images via Stain Deconvolution. - Maximilian Fischer; Peter Neher; Tassilo Wald; Silvia Dias Almeida; Shuhan Xiao; Peter J. Schüffler; Rickmer Braren; Michael Götz; Alexander Muckenhuber; Jens Kleesiek; Marco Nolden; Klaus H. Maier-Hein (MOVI@MICCAI, 2024)

A systematic review of machine learning-based tumor-infiltrating lymphocytes analysis in colorectal cancer: Overview of techniques, performance metrics, and clinical outcomes. - Azar Kazemi; Ashkan Rasouli-Saravani; Masoumeh Gharib; Tomé Albuquerque; Saeid Eslami; Peter J. Schüffler (Comput. Biol. Medicine, 2024)

Unlocking the Potential of Digital Pathology: Novel Baselines for Compression. - Maximilian Fischer; Peter Neher; Peter J. Schüffler; Sebastian Ziegler; Shuhan Xiao; Robin Peretzke; David A. Clunie; Constantin Ulrich; Michael Baumgartner 001; Alexander Muckenhuber; Silvia Dias Almeida; Michael Götz; et al. (CoRR, 2024)

Abstract: Learned Image Compression for HE-stained Histopathological Images via Stain Deconvolution. - Maximilian Fischer; Peter Neher; Tassilo Wald; Constantin Ulrich; Peter J. Schüffler; Shuhan Xiao; Silvia Dias Almeida; Alexander Muckenhuber; Rickmer Braren; Michael Götz; Jens Kleesiek; Marco Nolden; et al. (Bildverarbeitung für die Medizin, 2025)

Dataset Distillation with Probabilistic Latent Features. - Zhe Li 025; Sarah Cechnicka; Cheng Ouyang; Katharina Breininger; Peter J. Schüffler; Bernhard Kainz (CoRR, 2025)

HASD: Hierarchical Adaption for pathology Slide-level Domain-shift. - Jingsong Liu; Han Li; Chen Yang; Michael Deutges; Ario Sadafi; Xin You; Katharina Breininger; Nassir Navab; Peter J. Schüffler (CoRR, 2025)

Unit-Based Histopathology Tissue Segmentation via Multi-Level Feature Representation. - Ashkan Shakarami; Azade Farshad; Yousef Yeganeh; Lorenzo Nicolè; Peter J. Schüffler; Stefano Ghidoni; Nassir Navab (CoRR, 2025)