Schlagworte:
- adversarial learning
- Automatic segmentation
- Challenge
- Classification
- Computer Vision and Pattern Recognition (cs.CV)
- concept vectors
- cs.CV
- curriculum learning
- Deep convolutional neural network
- Deep Learning
- explainable AI (XAI)
- eye fundus images
- Feature ranking
- feature reuse
- finetuning
- FOS: Computer and information sciences
- glaucoma diagnosis
- Global explainability
- head and neck cancer
- Histopathology
- HPV status explanation. TNM explanation
- human-machine interaction
- interpretability
- Local explainability
- machine learning
- Machine Learning (cs.LG)
- medical imaging
- morphometric features
- multi-task learning
- Natural Language Processing
- Open access
- Oropharynx
- rule extraction
- wrong labels
Publikationen von Vincent Andrearczyk sortiert nach Zeitschrift und Typ
| 1-50 | 51-96 |
Publikationen vom Typ Inproceedings
2022
| , , , , , , , und , HEad and neCK TumOR segmentation and outcome prediction: The HECKTOR challenge, in: European Society of Radiology, 2022 |
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| , , , und , Multi-Organ Nucleus Segmentation Using a Locally Rotation Invariant Bispectral U-Net, in: Medical Imaging with Deep Learning, 2022 |
[URL] |
| , , , , , , , , , und , Overview of the HECKTOR Challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images, in: Head and Neck Tumor Segmentation and Outcome Prediction, Seiten 1-37, 2022 |
[DOI] [URL] |
| , , , , und , Segmentation and Classification of Head and Neck Nodal Metastases and Primary Tumors in PET/CT, in: 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Seiten 4731-4735, 2022 |
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| , , , , , und , The Image Biomarker Standardisation Initiative (IBSI) On Reproducible Convolutional Radiomics, in: European Society of Radiology, 2022 |
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2021
| , , und , Evaluation and Comparison of CNN Visual Explanations for Histopathology, in: XAI-AAAI-21, 2021 |
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| , , , , , und , Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT, in: Multimodal Learning for Clinical Decision Support, Seiten 59-68, Springer LNCS, 2021 |
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| , , , , , und , Multi-Task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer, in: 4th Workshop on PRedictive Intelligence in MEdicine, Seiten 147-156, Springer LNCS, 2021 |
[URL] |
, , , , , und , Radiomics Analysis Using The Image Biomarker Standardization Initiative (IBSI) Benchmarks And Guidelines, in: Radiological Society of North America (RSNA) 2021 Annual Meeting, 2021
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| , , , , und , Sharpening Local Interpretable Model-agnostic Explanations for Histopathology: Improved Understandability and Reliability, in: MICCAI 2021, Springer, 2021 |
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2020
| , , , , und , A systematic comparison of deep learning strategies for weakly supervised Gleason grading,, in: SPIE Medical Imaging, Houstonm, TX, USA, 2020 |
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| , , , , , , und , An Exploration of Uncertainty Information for Segmentation Quality Assessment, in: SPIE Medical Imaging 2020: Image Processing, Houston, TX, USA, Seiten 381-390, SPIE, 2020 |
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| , , , , , , , und , Automatic Segmentation of Head and Neck Tumors and Nodal Metastases in PET-CT scans, in: Medical Imaging with Deep Learning, Montréal, Canada, 2020 |
[URL] |
| , , und , Consistency of Scale Covariance in Internal Representations of CNNs, in: Irish Machine Vision and Image Processing Conference, 2020 |
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| , , , und , Exploiting the PubMed Central repository to mine out a large multimodal dataset of rare cancer studies, in: SPIE Medical Imaging, Houston, TX, USA, 2020 |
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| , , und , Generalizing Convolution Neural Networks on Stain Color Heterogeneous Data for Computational Pathology, in: SPIE Medical Imaging, Houston, TX, USA,, 2020 |
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| , , , und , Interpretable CNN Pruning for Preserving Scale-Covariant Features in Medical Imaging, in: Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI 2020, 2020 |
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| , und , Oropharynx Detection in PET-CT for Tumor Segmentation, in: Irish Machine Vision and Image Processing Conference, 2020, 2020 |
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| , , , , und , Training a deep neural network for small and highly heterogeneous MRID datasets for cancer grading, in: EMBC Conference, IEEE, 2020 |
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| , , , , und , Training Deep Neural Networks for Small and Highly Heterogeneous MRI Datasets for Cancer Grading, in: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC), IEEE, Seiten 1758--1761, 2020 |
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| , , , , und , Using Publicly Available Medical Images from the Open Access Literature and Social Networks for Model Training and Knowledge Extraction, in: Multimedia Modeling (MMM 2020), Seoul, Korea, 2020 |
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2019
, , , und , Exploring local rotation invariance in 3D CNNs with steerable filters, in: Medical Imaging with Deep Learning, Seiten 15-26, Proceedings of Machine Learning Research, 2019
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[URL] |
| , , , , , , , , , , , , , , , , , , , , , , , , und , ImageCLEF 2019: Multimedia Retrieval in Medical Nature, Security and Lifelogging Applications, in: ECIR 2019, Cologne, Germany, 2019 |
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| , , , , , , , , und , Improved interpretability for computer-aided severity assessment of retinopathy of prematurity, in: SPIE Medical Imaging, San Diego, CA, USA, 2019 |
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| , und , Interpreting intentionally flawed models with linear probes, in: ICCV workshop on statistical deep learning in computer vision, Seoul, Korea, 2019 |
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| , und , Learning Cross-Protocol Radiomics and Deep Feature Standardization from CT Images of Texture Phantoms, in: SPIE Medical Imaging 2019, International Society for Optics and Photonics, Seiten 109-116, SPIE, 2019 |
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| , , , und , Solid Spherical Energy (SSE) CNNs for Efficient 3D Medical Image Analysis, in: Irish Machine Vision and Image Processing Conference, Seiten 37-44, 2019 |
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| , und , Visualizing and interpreting feature reuse of pretrained CNNs for histopathology, in: IMVIP 2019, Dublin, Ireland, 2019 |
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2018
| und , Deep Multimodal Classification of Image Types in Biomedical Journal Figures, in: CLEF 2018, Avignon, France, Springer, 2018 |
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| , , , und , Glaucoma Diagnosis from Eye Fundus Images Based on Deep Morphometric Feature Estimation, in: OMIA at MICCAI, Granada, Spain, 2018 |
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| , , und , Image Magnification Regression Using DenseNet for Exploiting Histopathology Open Access Content, in: MICCAI 2018 - Computational Pathology Workshop (COMPAY), Granada, Spain, 2018 |
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| , , , , , , , , , , , , , , , , , , und , Overview of ImageCLEF 2018: Challenges, Datasets and Evaluation, in: CLEF conference proceeding, Avignon, France, Springer, 2018 |
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| , , und , Overview of the ImageCLEF 2018 caption prediction tasks, in: CLEF working notes, CEUR, 2018 |
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| , , , und , Rotation Invariance and Directional Sensitivity: Spherical Harmonics versus Radiomics Features, in: Machine Learning in Medical Imaging (MLMI), Seiten 107--115, Springer International Publishing, 2018 |
[URL] |
2021
| , , , , , , und , Overview of the HECKTOR Challenge at MICCAI 2020: Automatic Head and Neck Tumor Segmentation in PET/CT, Seiten 1-21, 2021 |
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Publikationen vom Typ Misc
2025
| , , , , , , , , , , und , AI-based Prediction of Myocardium Viability Using [82Rb] PET/CT, 2025 |
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| , , , , , , , , und , Left Ventricle Segmentation in Dynamic 82Rb PET/CT Using Deep Convolutional Neural Networks, 2025 |
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2023
| , , , und , Concept discovery and Dataset exploration with Singular Value Decomposition, ICLR Workshop on Trustworthy ML, 2023 |
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| , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , und , MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision, 2023 |
[URL] |
2020
, , , und , 3D Solid Spherical Bispectrum CNNs for Biomedical Texture Analysis, 2020
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[URL] |
| , , und , Guiding CNNs towards Relevant Concepts by Multi-task and Adversarial Learning, arxiv, 2020 |
[URL] |
| , , , , , , und , Standardised convolutional filtering for radiomics, 2020 |
[URL] |
Publikationen vom Typ Proceedings
2023
| , , und , Head and Neck Tumor Segmentation and Outcome Prediction, Springer International Publishing, 2023 |
[DOI] [URL] |
2022
| Head and Neck Tumor Segmentation and Outcome Prediction, Springer International Publishing, 2022 |
[DOI] [URL] |
2021
| Head and Neck Tumor Segmentation, Springer International Publishing, 2021 |
[URL] |
Publikationen vom Typ Unpublished
| 1-50 | 51-96 |