Ruining Deng on Muck Rack

Ruining Deng

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Articles

Evaluating cell AI foundation models in kidney pathology with human-in-the-loop enrichment - Communications Medicine

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By Junlin Guo, Ruining Deng, Catie Chang, Marilyn Lionts
| Nature Verified
Abstract Large-scale artificial intelligence foundation models have emerged as promising tools for addressing healthcare challenges, including digital pathology. While many have been developed for complex tasks such as disease diagnosis and tissue quantification using extensive and diverse datasets, their readiness for seemingly simpler tasks, such as nuclei segmentation within a single organ (for example, the kidney), remains unclear.
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[2508.15751] Fine-grained Multi-class Nuclei Segmentation with Molecular-empowered All-in-SAM Model

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By Can Cui, Ruining Deng, Yucheng Tang, Quan Liu
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Open in Who Shared View Duplicates (440) Issue with article?

[2309.02563] Evaluation Kidney Layer Segmentation on Whole Slide Imaging using Convolutional Neural Networks and Transformers

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By Chenyang Qi, Shunxing Bao, Quan Liu, Ruining Deng
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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