Jan Egger
Team Lead AI-guided Therapies
Institute for AI in Medicine, Germany
Jan has over 10 years of experience in developing algorithms in medical image analysis and image-guided therapies, including 5 years of postdoctoral research and development in the healthcare industry. Until now, he has published over 150 peer-reviewed papers, edited several books and won numerous awards for the theses and publications. He is also the PI of the open science client/server-based medical platform [StudierFenster] (www.studierfenster.at) and is mentoring the transition of the medical Augmented Reality FWF-project “enFaced” into the Start-up “Augmentomy”. During his career, he supervised and co-supervised around 100 student theses and projects, and was involved in the acquisition of over 14 million euros in third party funding. He holds a Ph.D. and a (German) Habilitation in Computer Science, and an interdisciplinary Ph.D. in Human Biology. Currently, Jan is a Privatdozent at the Technical University of Graz and a research group leader at the Institute for Artificial Intelligence in Medicine (IKIM) at the Essen University Hospital.
Latest
- Results from the autoPET challenge on fully automated lesion segmentation in oncologic PET/CT imaging
- Establishing Medical Intelligence - Leveraging FHIR to Improve Clinical Management: a retrospective cohort and clinical implementation study
- Cyto R-CNN and CytoNuke Dataset: Towards reliable whole-cell segmentation in bright-field histological images
- Der mobile Patient
- Multisensory Extended Reality Applications Offer Benefits for Volumetric Biomedical Image Analysis in Research and Medicine
- Deep Learning-based Point Cloud Registration for Augmented Reality-guided Surgery
- GAN-based generation of realistic 3D volumetric data: A systematic review and taxonomy
- Advancing Healthcare Through Open Science: StudierFenster and MedShapeNet
- Deep PCCT: Photon Counting Computed Tomography Deep Learning Applications Review
- Diminished Reality for Emerging Applications in Medicine through Inpainting
- Accelerating Artificial Intelligence-based Whole Slide Image Analysis with an Optimized Preprocessing Pipeline
- ChatGPT in healthcare: A taxonomy and systematic review
- CytoNuke Dataset: Towards reliable whole-cell segmentation in bright-field histological images
- Deep Interactive Segmentation of Medical Images: A Systematic Review and Taxonomy
- Designing and Implementing an Interactive Cloud Platform for Teaching Machine Learning with Medical Data
- Designing and Implementing an Interactive Cloud Platform for Teaching Machine Learning with Medical Data
- k-strip: A novel segmentation algorithm in k-space for the application of skull stripping
- What is Diminished Virtuality? A Directional and Layer-Based Taxonomy for the Reality-Virtuality Continuum
- 3D surgical instrument collection for computer vision and extended reality
- 3D-COSI ~ 3D Collection of Surgical Instruments
- Decoding pan-cancer treatment outcomes using multimodal real-world data and explainable artificial intelligence
- Anatomy Completor: A Multi-class Completion Framework for 3D Anatomy Reconstruction
- Improvement in Disease Diagnosis in Computed Tomography Images by Correlating Organ Volumes with Disease Occurrences in Humans
- Virtual Reality, Augmented Reality, Augmented Virtuality, or Mixed Reality in Cardiopulmonary Resuscitation: Which Extended Reality am I Using for Teaching Adult Basic Life Support?
- Apple Vision Pro for Healthcare: \"The Ultimate Display\"?
- Histology-Based Prediction of Therapy Response to Neoadjuvant Chemotherapy for Esophageal and Esophagogastric Junction Adenocarcinomas Using Deep Learning
- MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
- Information extraction from weakly structured radiological reports with natural language queries
- Open-source skull reconstruction with MONAI
- CellViT: Vision Transformers for Precise Cell Segmentation and Classification
- Establishing Medical Intelligence - Leveraging FHIR to Improve Clinical Management
- The autoPET challenge: Towards fully automated lesion segmentation in oncologic PET/CT imaging
- Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the AutoImplant 2021 cranial implant design challenge
- Valuing vicinity: Memory attention framework for context-based semantic segmentation in histopathology
- An Opinion on ChatGPT in Health Care—Written by Humans Only
- ChatGPT in Healthcare: A Taxonomy and Systematic Review
- Histology-based Prediction of Therapy Response to Neoadjuvant Chemotherapy for Esophageal and Esophagogastric Junction Adenocarcinomas Using Deep Learning
- A web-based radiomics module for image feature extraction for tumor characterization
- Evaluation of thresholding methods for the quantifcation of 68Ga‑PSMA‑11 PET molecular tumor volume and their efect on survival prediction in patients with advanced prostate cancer undergoing 177Lu‑PSMA‑617 radioligand therapy
- FAM: Relative Flatness Aware Minimization
- Lean Study Host: Towards an Automated Pipeline for Multi-Center Study Hosting
- On the Impact of Cross-Domain Data on German Language Models
- The HoloLens in medicine: A systematic review and taxonomy
- Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundaries
- Open-Source Skull Reconstruction with MONAI
- 'A net for everyone': fully personalized and unsupervised neural networks trained with longitudinal data from a single patient
- Valuing Vicinity: Memory attention framework for context-based semantic segmentation in histopathology
- The HoloLens in Medicine: A systematic Review and Taxonomy
- Training beta-VAE by Aggregating a Learned Gaussian Posterior with a Decoupled Decoder
- Deep Learning–driven classification of external DICOM studies for PACS archiving
- GAN-based generation of realistic 3D data: A systematic review and taxonomy
- k-strip: A novel segmentation algorithm in k-space for the application of skull stripping
- Medical Deep Learning – A systematic Meta-Review
- Review of Disentanglement Approaches for Medical Applications: Towards Solving the Gordian Knot of Generative Models in Healthcare
- Stochastic Modeling of Inhomogeneities in the Aortic Wall and Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate
- Sparse Convolutional Neural Networks for Medical Image Analysis
- AVT: Multicenter aortic vessel tree CTA dataset collection with ground truth segmentation masks
- Beyond Medical Imaging-A Review of Multimodal Deep Learning in Radiology
- Radiomics in Head and Neck Cancer Outcome Predictions
- Studierfenster: an Open Science Cloud-Based Medical Imaging Analysis Platform
- Computer-Aided Oral and Maxillofacial Surgery: Developments, Applications, and Future Perspectives
- A web client-based online DICOM browser and NRRD converter for Studierfenster
- A cloud-based centerline algorithm for Studierfenster
- A patch-based-approach for aortic landmarking
- A review on patient-specific facial and cranial implant design using Artificial Intelligence (AI) techniques
- Ai-based aortic vessel tree segmentation for cardiovascular diseases treatment: status quo
- An online platform for automatic skull defect restoration and cranial implant design
- Augmented reality in oral and maxillofacial surgery
- Automated cross-sectional view selection in CT angiography of aortic dissections with uncertainty awareness and retrospective clinical annotations
- Deep learning and particle filter-based aortic dissection vessel tree segmentation
- Deep learning—a first meta-survey of selected reviews across scientific disciplines, their commonalities, challenges and research impact
- Effects of Pre-Operative Risk Factors on Intensive Care Unit Length of Stay (ICU-LOS) in Major Oral and Maxillofacial Cancer Surgery
- Inside-out instrument tracking for surgical navigation in augmented reality
- Learning to rearrange voxels in binary segmentation masks for smooth manifold triangulation
- Medical image segmentation in oral-maxillofacial surgery
- PCA-Skull: 3D Skull Shape Modelling Using Principal Component Analysis
- Radiomics in head and neck cancer
- SkullBreak/SkullFix–Dataset for automatic cranial implant design and a benchmark for volumetric shape learning tasks
- Sparse Convolutional Neural Network for Skull Reconstruction
- Synthetic skull bone defects for automatic patient-specific craniofacial implant design
- Towards the Automatization of Cranial Implant Design in Cranioplasty II
- Towards the automatization of cranial implant design in cranioplasty