collaborators

6 papers

cs.CV2026

An end-to-end-trained vision-language model for native-language prostate pathology report generation

Christian Grashei, Fabian Gülhan, Maximilian Legnar +4

Prostate cancer is among the most frequently diagnosed malignancies worldwide, and structured reporting of each biopsy core burdens pathologists. Existing tools frame this as class…

cs.CV2026

Paired Uterine Whole-Slide Images and Pathology Reports for Multimodal Computational Pathology

Han Li, Jingsong Liu, Ayako Ura +14

Uterine diseases represent an important category of gynecologic pathology and require accurate histopathological assessment for diagnosis and treatment planning. Whole-slide images…

cs.CV2026

Towards Cellular-Scale Interpretability in Pathology Foundation Models for Biomarker Assessment

Jingsong Liu, Han Li, Zhengyang Xu +19

Molecular biomarker testing in pathology is often costly and tissue-consuming, limiting scalable clinical deployment. Artificial intelligence applied to hematoxylin and eosin (HE)-…

cs.CV2026

Efficient Special Stain Classification

Oskar Thaeter, Christian Grashei, Anette Haas +3

Stains are essential in histopathology to visualize specific tissue characteristics, with Haematoxylin and Eosin (H&E) serving as the clinical standard. However, pathologists frequ…

cs.CV2025

Pathryoshka: Compressing Pathology Foundation Models via Multi-Teacher Knowledge Distillation with Nested Embeddings

Christian Grashei, Christian Brechenmacher, Rao Muhammad Umer +5

Pathology foundation models (FMs) have driven significant progress in computational pathology. However, these high-performing models can easily exceed a billion parameters and prod…

eess.IV2025

From Pixels to Pathology: Restoration Diffusion for Diagnostic-Consistent Virtual IHC

Jingsong Liu, Xiaofeng Deng, Han Li +8

Hematoxylin and eosin (H&E) staining is the clinical standard for assessing tissue morphology, but it lacks molecular-level diagnostic information. In contrast, immunohistochemistr…