most citedUnsupervised Learning for Feature Extraction and Temporal Alignment of 3D+t Point Clouds of Zebrafish Embryos

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Semantic-Guided Multimodal Preprocessing for Vision Transformer-Based Clear Cell Renal Cell Carcinoma Grading

Fatemeh Javadian, Zhu Chen, Zahra Aminparast +1

Clear cell renal cell carcinoma (CCRCC) grading is essential for treatment planning, yet existing approaches either analyze patch-level images directly or focus solely on nuclei-le…

cs.CV2025

Segment Anything for Cell Tracking

Zhu Chen, Mert Edgü, Er Jin +1

Tracking cells and detecting mitotic events in time-lapse microscopy image sequences is a crucial task in biomedical research. However, it remains highly challenging due to dividin…

cs.LG2025

CellStyle: Improved Zero-Shot Cell Segmentation via Style Transfer

Rüveyda Yilmaz, Zhu Chen, Yuli Wu +1

Cell microscopy data are abundant; however, corresponding segmentation annotations remain scarce. Moreover, variations in cell types, imaging devices, and staining techniques intro…

cs.CV2025★ 1 cited

Unsupervised Learning for Feature Extraction and Temporal Alignment of 3D+t Point Clouds of Zebrafish Embryos

Zhu Chen, Ina Laube, Johannes Stegmaier

Zebrafish are widely used in biomedical research and developmental stages of their embryos often need to be synchronized for further analysis. We present an unsupervised approach t…

cs.CV2025

No Free Lunch in Annotation either: An objective evaluation of foundation models for streamlining annotation in animal tracking

Emil Mededovic, Valdy Laurentius, Yuli Wu +5

We analyze the capabilities of foundation models addressing the tedious task of generating annotations for animal tracking. Annotating a large amount of data is vital and can be a…