Peter J. Schüffler

Orcid: 0000-0002-1353-8921

According to our database1, Peter J. Schüffler authored at least 40 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2024
Learned Image Compression for HE-stained Histopathological Images via Stain Deconvolution.
CoRR, 2024

A systematic review of machine learning-based tumor-infiltrating lymphocytes analysis in colorectal cancer: Overview of techniques, performance metrics, and clinical outcomes.
Comput. Biol. Medicine, 2024

Abstract: Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

2023

Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023

Whole Slide Multiple Instance Learning for Predicting Axillary Lymph Node Metastasis.
Proceedings of the Data Engineering in Medical Imaging - First MICCAI Workshop, 2023

DISBELIEVE: Distance Between Client Models Is Very Essential for Effective Local Model Poisoning Attacks.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023

Multimodal Context-Aware Detection of Glioma Biomarkers Using MRI and WSI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023

Abstract: Deep-learning on Lossily Compressed Pathology Images - Adverse Effects for ImageNet Pre-trained Models.
Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

2022
Deep Learning on Lossily Compressed Pathology Images: Adverse Effects for ImageNet Pre-trained Models.
Proceedings of the Medical Optical Imaging and Virtual Microscopy Image Analysis, 2022

DICOM Whole Slide Imaging for Computational Pathology Research in Kaapana and the Joint Imaging Platform.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

2021
Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images - The ACDC@LungHP Challenge 2019.
IEEE J. Biomed. Health Informatics, 2021

Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center.
J. Am. Medical Informatics Assoc., 2021

Quantifying Heterogeneity in Tumors: Proposing a New Method Utilizing Convolutional Neuronal Networks.
Proceedings of the Informatics and Technology in Clinical Care and Public Health, 2021

2020
Deep Learning Methods for Lung Cancer Segmentation in Whole-slide Histopathology Images - the ACDC@LungHP Challenge 2019.
CoRR, 2020

Deep Interactive Learning: An Efficient Labeling Approach for Deep Learning-Based Osteosarcoma Treatment Response Assessment.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2018
Towards machine learned quality control: A benchmark for sharpness quantification in digital pathology.
Comput. Medical Imaging Graph., 2018

2017
MRI-Based Surgical Planning for Lumbar Spinal Stenosis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

2016
Multi-Organ Cancer Classification and Survival Analysis.
CoRR, 2016

Mitochondria-based Renal Cell Carcinoma Subtyping: Learning from Deep vs. Flat Feature Representations.
Proceedings of the 1st Machine Learning in Health Care, 2016

DeepScope: Nonintrusive Whole Slide Saliency Annotation and Prediction from Pathologists at the Microscope.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2016

2015
Crohn's disease segmentation from MRI using learned image priors.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

2014
Semi-automatic Crohn's Disease Severity Estimation on MR Imaging.
Proceedings of the Abdominal Imaging. Computational and Clinical Applications, 2014

Combining Multiple Expert Annotations Using Semi-supervised Learning and Graph Cuts for Crohn's Disease Segmentation.
Proceedings of the Abdominal Imaging. Computational and Clinical Applications, 2014

Active learning based segmentation of Crohn's disease using principles of visual saliency.
Proceedings of the IEEE 11th International Symposium on Biomedical Imaging, 2014

2013
Automated Analysis of Tissue Micro-Array Images on the Example of Renal Cell Carcinoma.
Proceedings of the Similarity-Based Pattern Analysis and Recognition, 2013

Automatic Detection and Segmentation of Crohn's Disease Tissues From Abdominal MRI.
IEEE Trans. Medical Imaging, 2013

A Supervised Learning Approach for Crohn's Disease Detection Using Higher-Order Image Statistics and a Novel Shape Asymmetry Measure.
J. Digit. Imaging, 2013

Localizing and segmenting Crohn's disease affected regions in abdominal MRI using novel context features.
Proceedings of the Medical Imaging 2013: Image Processing, 2013

A Model Development Pipeline for Crohn's Disease Severity Assessment from Magnetic Resonance Images.
Proceedings of the Abdominal Imaging. Computation and Clinical Applications, 2013

Semi-Supervised and Active Learning for Automatic Segmentation of Crohn's Disease.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013

Weakly supervised semantic segmentation of Crohn's disease tissues from abdominal MRI.
Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

Crohn's disease tissue segmentation from abdominal MRI using semantic information and graph cuts.
Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

2012
A Supervised Learning Based Approach to Detect Crohn's Disease in Abdominal MR Volumes.
Proceedings of the Abdominal Imaging. Computational and Clinical Applications, 2012

Computational modeling for assessment of IBD: To be or not to be?
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

2011
Hybrid Generative-Discriminative Nucleus Classification of Renal Cell Carcinoma.
Proceedings of the Similarity-Based Pattern Recognition - First International Workshop, 2011

Combining Data Sources Nonlinearly for Cell Nucleus Classification of Renal Cell Carcinoma.
Proceedings of the Similarity-Based Pattern Recognition - First International Workshop, 2011

Renal Cancer Cell Classification Using Generative Embeddings and Information Theoretic Kernels.
Proceedings of the Pattern Recognition in Bioinformatics, 2011

A Multiple Kernel Learning Algorithm for Cell Nucleus Classification of Renal Cell Carcinoma.
Proceedings of the Image Analysis and Processing - ICIAP 2011, 2011

2010
Computational TMA Analysis and Cell Nucleus Classification of Renal Cell Carcinoma.
Proceedings of the Pattern Recognition, 2010


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