Jan S. Kirschke
Professor
Develops AI-based automated image processing and image-based biomarkers in neuroradiology, including spine imaging.
Jan S. Kirschke's lab at TUM works on medical imaging & healthcare AI. 21 papers since 2023, 5 at top venues, mostly MICCAI and ISBI.
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 24%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 5 papers2026 · T1 2 · collecting
- 4 papers2025 · T1 1
- 5 papers2024 · T1 0
- 7 papers2023 · T1 2
T1 venuesOtherVenues: MICCAI, ISBI, ICLR, IPMI, npj Digit. Medicine
Research focuspaper titles that use each topic's words
- Medical imaging & healthcare AI1 paper
- image-based0 papers
- biomarkers0 papers
- ai-based0 papers
- tum0 papers
Paper list
From DBLP.
20265 papers
- Comput. Biol. MedicineGeometry alone? Evaluating the predictive capability of morphed intervertebral disc FEM models with a single material configuration (opens in a new tab)
- MICCAI (T1)One Sequence to Segment Them All: Efficient Data Augmentation for CT and MRI Cross-Domain 3D Spine Segmentation (opens in a new tab)
- Comput. Biol. MedicinePARASIDE: An automatic paranasal sinus segmentation and structure analysis tool for magnetic resonance imaging (opens in a new tab)
- ICLR (T1)Reliable Evaluation of MRI Motion Correction: Dataset and Insights (opens in a new tab)
- npj Digit. MedicineWhole body CT attenuation and volume charts from routine clinical scans via LLM report filtering (opens in a new tab)
20254 papers
- MICCAI (T1)MAGO-SP: Detection and Correction of Water-Fat Swaps in Magnitude-Only VIBE MRI (opens in a new tab)
- Comput. Biol. MedicineNeural network surrogate and projected gradient descent for fast and reliable finite element model calibration: A case study on an intervertebral disc (opens in a new tab)
- DT4H@MICCAIRule-based Key-Point Extraction for MR-Guided Biomechanical Digital Twins of the Spine (opens in a new tab)
- NeuroImageTowards quantitative intensity analysis of conventional T1-weighted images in multiple sclerosis (opens in a new tab)
20245 papers
- BMC Medical ImagingAutomated assessment of cardiac pathologies on cardiac MRI using T1-mapping and late gadolinium phase sensitive inversion recovery sequences with deep learning (opens in a new tab)
- ISIC/iMIMIC/EARTH/DeCaF@MICCAIDetecting Unforeseen Data Properties with Diffusion Autoencoder Embeddings Using Spine MRI Data (opens in a new tab)
- MIDLModeling the acquisition shift between axial and sagittal MRI for diffusion superresolution to enable axial spine segmentation (opens in a new tab)
- J. Imaging Inform. MedicineRobust Ensemble of Two Different Multimodal Approaches to Segment 3D Ischemic Stroke Segmentation Using Brain Tumor Representation Among Multiple Center Datasets (opens in a new tab)
- MIDLVideo-CT MAE: Self-supervised Video-CT Domain Adaptation for Vertebral Fracture Diagnosis (opens in a new tab)
20237 papers
- MICCAI (T1)3D Arterial Segmentation via Single 2D Projections and Depth Supervision in Contrast-Enhanced CT Images (opens in a new tab)
- ISBIApproaching Peak Ground Truth (opens in a new tab)
- IPMIblob loss: Instance Imbalance Aware Loss Functions for Semantic Segmentation (opens in a new tab)
- BrainLes/SWITCH@MICCAIPrimitive Simultaneous Optimization of Similarity Metrics for Image Registration (opens in a new tab)
- ISBIPushing the Limits of an FCN and A CRF Towards Near-Ideal Vertebrae Labelling (opens in a new tab)
- MICCAI (T1)Single-subject Multi-contrast MRI Super-resolution via Implicit Neural Representations (opens in a new tab)
- Medical Image Anal.The Liver Tumor Segmentation Benchmark (LiTS) (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to TUMRolling
Not announced yet
Computer Science Doctorate (CIT)
- Round
- Rolling (position-based)
- Opens
- —
- GRE
- See program page
- English
- Very good written and spoken English; no minimum test score
- Fee
- See program page
Confirmed on the program page.
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Data
Some numbers could not be verified:
- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
- Collected
- Verified
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- DBLP
- Members
- Not collected
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.