Geert Litjens
Orcid: 0000-0003-1554-1291Affiliations:
- Radboud University Medical Center, Diagnostic Image Analysis Group and the Department of Pathology, Nijmegen, The Netherlands
According to our database1,
Geert Litjens
authored at least 74 papers
between 2010 and 2024.
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Bibliography
2024
Automatic data augmentation to improve generalization of deep learning in H&E stained histopathology.
Comput. Biol. Medicine, March, 2024
IEEE J. Biomed. Health Informatics, January, 2024
Medical Image Anal., 2024
Detection and subtyping of basal cell carcinoma in whole-slide histopathology using weakly-supervised learning.
Medical Image Anal., 2024
Navigating the landscape of multimodal AI in medicine: a scoping review on technical challenges and clinical applications.
CoRR, 2024
Masked Attention as a Mechanism for Improving Interpretability of Vision Transformers.
CoRR, 2024
CoRR, 2024
2023
Medical Image Anal., August, 2023
Continual learning strategies for cancer-independent detection of lymph node metastases.
Medical Image Anal., April, 2023
Predictive uncertainty estimation for out-of-distribution detection in digital pathology.
Medical Image Anal., 2023
Hierarchical Vision Transformers for Context-Aware Prostate Cancer Grading in Whole Slide Images.
CoRR, 2023
PythoStitcher: an iterative approach for stitching digitized tissue fragments into full resolution whole-mount reconstructions.
Proceedings of the Medical Imaging 2023: Digital and Computational Pathology, 2023
2022
Streaming Convolutional Neural Networks for End-to-End Learning With Multi-Megapixel Images.
IEEE Trans. Pattern Anal. Mach. Intell., 2022
Domain adaptation strategies for cancer-independent detection of lymph node metastases.
CoRR, 2022
CoRR, 2022
Prostate158 - An expert-annotated 3T MRI dataset and algorithm for prostate cancer detection.
Comput. Biol. Medicine, 2022
Proceedings of the Medical Imaging 2022: Digital and Computational Pathology, 2022
2021
Detection of Prostate Cancer in Whole-Slide Images Through End-to-End Training With Image-Level Labels.
IEEE Trans. Medical Imaging, 2021
Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images - The ACDC@LungHP Challenge 2019.
IEEE J. Biomed. Health Informatics, 2021
IEEE Trans. Pattern Anal. Mach. Intell., 2021
Residual cyclegan for robust domain transformation of histopathological tissue slides.
Medical Image Anal., 2021
End-to-end classification on basal-cell carcinoma histopathology whole-slides images.
Proceedings of the Medical Imaging 2021: Digital Pathology, Online, February 15-19, 2021, 2021
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021
2020
Deep Learning Methods for Lung Cancer Segmentation in Whole-slide Histopathology Images - the ACDC@LungHP Challenge 2019.
CoRR, 2020
Artificial Intelligence Assistance Significantly Improves Gleason Grading of Prostate Biopsies by Pathologists.
CoRR, 2020
Predicting MYC translocation in HE specimens of diffuse large B-cell lymphoma through deep learning.
Proceedings of the Medical Imaging 2020: Digital Pathology, 2020
Multi-class semantic cell segmentation and classification of aplasia in bone marrow histology images.
Proceedings of the Medical Imaging 2020: Digital Pathology, 2020
Efficient Out-of-Distribution Detection in Digital Pathology Using Multi-Head Convolutional Neural Networks.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020
2019
From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge.
IEEE Trans. Medical Imaging, 2019
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology.
Medical Image Anal., 2019
Medical Image Anal., 2019
Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands.
CoRR, 2019
Dealing with Label Scarcity in Computational Pathology: A Use Case in Prostate Cancer Classification.
CoRR, 2019
A large annotated medical image dataset for the development and evaluation of segmentation algorithms.
CoRR, 2019
High resolution whole prostate biopsy classification using streaming stochastic gradient descent.
Proceedings of the Medical Imaging 2019: Digital Pathology, 2019
Stain-Transforming Cycle-Consistent Generative Adversarial Networks for Improved Segmentation of Renal Histopathology.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2019
2018
Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks.
IEEE Trans. Medical Imaging, 2018
Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard.
CoRR, 2018
Unsupervised Prostate Cancer Detection on H&E using Convolutional Adversarial Autoencoders.
CoRR, 2018
CoRR, 2018
H&E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection.
Proceedings of the Medical Imaging 2018: Digital Pathology, 2018
Proceedings of the Medical Imaging 2018: Digital Pathology, 2018
Automated segmentation of epithelial tissue in prostatectomy slides using deep learning.
Proceedings of the Medical Imaging 2018: Digital Pathology, 2018
Automatic segmentation of histopathological slides of renal tissue using deep learning.
Proceedings of the Medical Imaging 2018: Digital Pathology, 2018
Structure Instance Segmentation in Renal Tissue: A Case Study on Tubular Immune Cell Detection.
Proceedings of the Computational Pathology and Ophthalmic Medical Image Analysis, 2018
2017
Medical Image Anal., 2017
Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images.
CoRR, 2017
Int. J. Comput. Assist. Radiol. Surg., 2017
The importance of stain normalization in colorectal tissue classification with convolutional networks.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
Comparison of different methods for tissue segmentation in histopathological whole-slide images.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
2016
Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks.
IEEE Trans. Medical Imaging, 2016
IEEE Trans. Medical Imaging, 2016
IEEE Trans. Medical Imaging, 2016
Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities.
CoRR, 2016
Automated robust registration of grossly misregistered whole-slide images with varying stains.
Proceedings of the Medical Imaging 2016: Digital Pathology, San Diego, California, United States, 27 February, 2016
2015
Automated detection of prostate cancer in digitized whole-slide images of H and E-stained biopsy specimens.
Proceedings of the Medical Imaging 2015: Digital Pathology, 2015
A multi-scale superpixel classification approach to the detection of regions of interest in whole slide histopathology images.
Proceedings of the Medical Imaging 2015: Digital Pathology, 2015
2014
IEEE Trans. Medical Imaging, 2014
Medical Image Anal., 2014
Distinguishing benign confounding treatment changes from residual prostate cancer on MRI following laser ablation.
Proceedings of the Medical Imaging 2014: Image-Guided Procedures, 2014
Distinguishing prostate cancer from benign confounders via a cascaded classifier on multi-parametric MRI.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, San Diego, 2014
2012
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012
Automated computer-aided detection of prostate cancer in MR images: from a whole-organ to a zone-based approach.
Proceedings of the Medical Imaging 2012: Computer-Aided Diagnosis, San Diego, 2012
2011
Proceedings of the Prostate Cancer Imaging. Image Analysis and Image-Guided Interventions, 2011
Automatic computer aided detection of abnormalities in multi-parametric prostate MRI.
Proceedings of the Medical Imaging 2011: Computer-Aided Diagnosis, 2011
2010
Simulation of Nodules and Diffuse Infiltrates in Chest Radiographs Using CT Templates.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2010
Computer Aided Detection of Prostate Cancer Using T2, DWI and DCE MRI: Methods and Clinical Applications.
Proceedings of the Prostate Cancer Imaging. Computer-Aided Diagnosis, 2010
Pharmacokinetic models in clinical practice: what model to use for DCE-MRI of the breast?
Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010