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Jan Kirschke

Identifiers

  • name variant Jan Kirschke 0.60 · backfill

Papers (21)

  1. Routine laboratory trajectories encode the onset of organ-level complications in cancer cs.LG · 2026 · author #19
  2. Redefining Instance Matching: A Unified Framework for Part-Aware Matching in Panoptic Segmentation Evaluation cs.CV · 2026 · author #9
  3. Whole-body CT attenuation and volume charts from routine clinical scans via evidence-grounded LLM report filtering cs.CV · 2026 · author #4
  4. BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis cs.CV · 2025 · author #24
  5. BraTS orchestrator : Democratizing and Disseminating state-of-the-art brain tumor image analysis eess.IV · 2025 · author #12
  6. MAGO-SP: Detection and Correction of Water-Fat Swaps in Magnitude-Only VIBE MRI cs.CV · 2025 · author #18
  7. PARASIDE: An Automatic Paranasal Sinus Segmentation and Structure Analysis Tool for MRI cs.CV · 2025 · author #11
  8. Enhancing Interpretability of Vertebrae Fracture Grading using Human-interpretable Prototypes cs.CV · 2024 · author #8
  9. Numerical simulation of individual coil placement -- A proof-of-concept study for the prediction of recurrence after aneurysm coiling cs.CE · 2024 · author #7
  10. Numerical simulation of endovascular treatment options for cerebral aneurysms math.NA · 2024 · author #4
  11. The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting eess.IV · 2023 · author #64
  12. Approaching Peak Ground Truth cs.LG · 2022 · author #14
  13. CheXplaining in Style: Counterfactual Explanations for Chest X-rays using StyleGAN eess.IV · 2022 · author #6
  14. Deep Quality Estimation: Creating Surrogate Models for Human Quality Ratings cs.CV · 2022 · author #13
  15. blob loss: instance imbalance aware loss functions for semantic segmentation cs.CV · 2022 · author #12
  16. A Deep Learning Approach to Predicting Collateral Flow in Stroke Patients Using Radiomic Features from Perfusion Images cs.CV · 2021 · author #4
  17. Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient eess.IV · 2021 · author #17
  18. The Liver Tumor Segmentation Benchmark (LiTS) cs.CV · 2019 · author #31
  19. Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge cs.CV · 2018 · author #19
  20. Multi-Scale Convolutional-Stack Aggregation for Robust White Matter Hyperintensities Segmentation cs.CV · 2018 · author #4
  21. DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes cs.CV · 2018 · author #5

Mentions

  • 2507.09036 #24 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2506.13807 #12 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2502.14659 #18 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2501.14514 #11 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2305.08992 #64 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2404.02830 #8 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2402.00550 #4 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2403.06889 #7 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2205.08209 #12 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2103.06205 #17 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2301.00243 #14 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 1901.04056 #31 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2205.10355 #13 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2207.07553 #6 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2110.12508 #4 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 1803.09340 #5 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 1807.05153 #4 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2606.08538 #19 · arxiv_oai · confidence 0.70 Jan Kirschke
  • 2605.31094 #9 · arxiv_oai · confidence 0.70 Jan Kirschke

Frequent Coauthors