Julia Schnabel
Professor
Researches medical image computing and machine learning, including motion modelling, image reconstruction, quality control and segmentation of multi-modal images.
Julia Schnabel's lab at TUM works on medical imaging & healthcare AI, 3D vision & neural rendering and recognition, detection & segmentation. 69 papers since 2023, 17 at top venues, mostly MICCAI and ISBI. 14 PhD students.
At a glance
- papers, 2023–2026
- 18/ year
- at T1 venues
- 25%
- PhD students
- 14
- MS students
- 0
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 17 papers2026 · T1 1 · collecting
- 9 papers2025 · T1 4
- 28 papers2024 · T1 9
- 15 papers2023 · T1 3
T1 venuesOtherVenues: MICCAI, ISBI, WACV, ECCV, ICCV
Research focuspaper titles that use each topic's words
- Recognition, detection & segmentation19 papers
- Medical imaging & healthcare AI17 papers
- 3D vision & neural rendering13 papers
- researches medical0 papers
- image computing0 papers
Paper list
From DBLP.
202617 papers
- Bildverarbeitung für die MedizinAbstract: Progressive Growing of Patch Size - Curriculum Learning for Accelerated, Improved Medical Image Segmentation (opens in a new tab)
- ISBICovariance Descriptors Meet General Vision Encoders: Riemannian Deep Learning for Medical Image Classification (opens in a new tab)
- Medical Image Anal.Fréchet radiomic distance (FRD): A versatile metric for comparing medical imaging datasets (opens in a new tab)
- Medical Image Anal.From model based to learned regularization in medical image registration: A comprehensive review (opens in a new tab)
- MICCAI (T1)Gabor Primitives for Accelerated Cardiac Cine MRI Reconstruction (opens in a new tab)
- WACVHierarchical Adaptive networks with Task vectors for Test-Time Adaptation (opens in a new tab)
- WACVKnowledge to Sight: Reasoning over Visual Attributes via Knowledge Decomposition for Abnormality Grounding (opens in a new tab)
- ISBILearning to Reason About Rare Diseases Through Retrieval-Augmented Agents (opens in a new tab)
- ISBILOCBAM: Advancing 3D Patch-Based Image Segmentation by Integrating Location Context (opens in a new tab)
- Bildverarbeitung für die MedizinMaster Class on Reproducibility - A Student Hackathon on Advanced MRI Reconstruction Methods (opens in a new tab)
- ISBIMeasuring and Aligning Abstraction in Vision-Language Models with Medical Taxonomies (opens in a new tab)
- Medical Image Anal.PISCO: Self-supervised k-space regularization for improved neural implicit k-space representations of dynamic MRI (opens in a new tab)
20259 papers
- ISBICellPilot: A Unified Approach to Automatic and Interactive Segmentation in Histopathology (opens in a new tab)
- EMERGE@MICCAIGroundingDINO for Open-Set Lesion Detection in Medical Imaging (opens in a new tab)
- IEEE J. Biomed. Health InformaticsGuest Editorial: Special Issue on Foundation Models in Medical Imaging (opens in a new tab)
- MICCAI (T1)Influence of Classification Task and Distribution Shift Type on OOD Detection in Fetal Ultrasound (opens in a new tab)
- GRAIL/RIME@MICCAIINR Meets Multi-contrast MRI Reconstruction (opens in a new tab)
- MICCAI (T1)Lightweight Data-Free Denoising for Detail-Preserving Biomedical Image Restoration (opens in a new tab)
- NeurIPS (T1)NOVA: A Benchmark for Rare Anomaly Localization and Clinical Reasoning in Brain MRI (opens in a new tab)
- IPMISubspace Implicit Neural Representations for Real-Time Cardiac Cine MR Imaging (opens in a new tab)
- MICCAI (T1)Temporal Neural Cellular Automata: Application to Modeling of Contrast Enhancement in Breast MRI (opens in a new tab)
202428 papers
- IEEE Trans. Biomed. Eng.A Deep Learning-Based Integrated Framework for Quality-Aware Undersampled Cine Cardiac MRI Reconstruction and Analysis (opens in a new tab)
- WBIRA Self-supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer (opens in a new tab)
- HealthComAdvancing Neonatal Care: A Deep Learning Approach for Non-Contact Heart Rate Monitoring (opens in a new tab)
- ISIC/iMIMIC/EARTH/DeCaF@MICCAIComplex-Valued Federated Learning with Differential Privacy and MRI Applications (opens in a new tab)
- MICCAI (T1)Data-Driven Tissue- and Subject-Specific Elastic Regularization for Medical Image Registration (opens in a new tab)
- IEEE Trans. Medical ImagingDeep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review (opens in a new tab)
- ToothFairy/3DTeethLand/STS@MICCAIDiENTeS: Dynamic ENTity Segmentation with Local-Global Transformers (opens in a new tab)
- ASMUS@MICCAIDiffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound (opens in a new tab)
- MICCAI (T1)Diffusion Models with Implicit Guidance for Medical Anomaly Detection (opens in a new tab)
- MICCAI (T1)DinoBloom: A Foundation Model for Generalizable Cell Embeddings in Hematology (opens in a new tab)
- Deep-Breath@MICCAIEnhancing the Utility of Privacy-Preserving Cancer Classification Using Synthetic Data (opens in a new tab)
- ECCV (T1)Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations (opens in a new tab)
202315 papers
- ICCV (T1)A skeletonization algorithm for gradient-based optimization (opens in a new tab)
- CLIP/FAIMI/EPIMI@MICCAIBias in Unsupervised Anomaly Detection in Brain MRI (opens in a new tab)
- EMBCColorimetric Sensor Reading and Illumination Correction via Multi-Task Deep-Learning (opens in a new tab)
- MICADEvaluation of Randomized Input Sampling for Explanation (RISE) for 3D XAI - Proof of Concept for Black-Box Brain-Hemorrhage Classification (opens in a new tab)
- ISBIF2FD: Fourier Perturbations for Denoising Cryo-Electron Tomograms and Comparison to Established Approaches (opens in a new tab)
- Medical Image Anal.Fast fetal head compounding from multi-view 3D ultrasound (opens in a new tab)
- MIDLGeneralizing Unsupervised Anomaly Detection: Towards Unbiased Pathology Screening (opens in a new tab)
- DGM4MICCAIICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space (opens in a new tab)
- CaPTion@MICCAIMultispectral 3D Masked Autoencoders for Anomaly Detection in Non-Contrast Enhanced Breast MRI (opens in a new tab)
- SASHIMI@MICCAIPhysics-Aware Motion Simulation For T2*-Weighted Brain MRI (opens in a new tab)
- Medical Image Anal.Placenta segmentation in ultrasound imaging: Addressing sources of uncertainty and limited field-of-view (opens in a new tab)
- MICCAI (T1)Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
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Computer Science Doctorate (CIT)
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- Very good written and spoken English; no minimum test score
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