4 citations · 9 across the 20 of their papers we have counts for
13 papers · 1 filter
Glo-In-One-v2: Holistic Identification of Glomerular Cells, Tissues, and Lesions in Human and Mouse Histopathology
Lining Yu, Mengmeng Yin, Ruining Deng +9
Segmenting glomerular intraglomerular tissue and lesions traditionally depends on detailed morphological evaluations by expert nephropathologists, a labor-intensive process suscept…
Evaluating Cell AI Foundation Models in Kidney Pathology with Human-in-the-Loop Enrichment
Junlin Guo, Siqi Lu, Can Cui +14
Training AI foundation models has emerged as a promising large-scale learning approach for addressing real-world healthcare challenges, including digital pathology. While many of t…
Assessment of Cell Nuclei AI Foundation Models in Kidney Pathology
Junlin Guo, Siqi Lu, Can Cui +14
Cell nuclei instance segmentation is a crucial task in digital kidney pathology. Traditional automatic segmentation methods often lack generalizability when applied to unseen datas…
Large-scale cervical precancerous screening via AI-assisted cytology whole slide image analysis
Honglin Li, Yusuan Sun, Chenglu Zhu +8
Cervical Cancer continues to be the leading gynecological malignancy, posing a persistent threat to women's health on a global scale. Early screening via cytology Whole Slide Image…
PFPs: Prompt-guided Flexible Pathological Segmentation for Diverse Potential Outcomes Using Large Vision and Language Models
Can Cui, Ruining Deng, Junlin Guo +4
The Vision Foundation Model has recently gained attention in medical image analysis. Its zero-shot learning capabilities accelerate AI deployment and enhance the generalizability o…
HoloHisto: End-to-end Gigapixel WSI Segmentation with 4K Resolution Sequential Tokenization
Yucheng Tang, Yufan He, Vishwesh Nath +11
In digital pathology, the traditional method for deep learning-based image segmentation typically involves a two-stage process: initially segmenting high-resolution whole slide ima…
GLAM: Glomeruli Segmentation for Human Pathological Lesions using Adapted Mouse Model
Lining Yu, Mengmeng Yin, Ruining Deng +9
Moving from animal models to human applications in preclinical research encompasses a broad spectrum of disciplines in medical science. A fundamental element in the development of…
Dataset Distillation in Medical Imaging: A Feasibility Study
Muyang Li, Can Cui, Quan Liu +4
Data sharing in the medical image analysis field has potential yet remains underappreciated. The aim is often to share datasets efficiently with other sites to train models effecti…
Data-driven Nucleus Subclassification on Colon H&E using Style-transferred Digital Pathology
Lucas W. Remedios, Shunxing Bao, Samuel W. Remedios +16
Understanding the way cells communicate, co-locate, and interrelate is essential to furthering our understanding of how the body functions. H&E is widely available, however, cell s…
HATs: Hierarchical Adaptive Taxonomy Segmentation for Panoramic Pathology Image Analysis
Ruining Deng, Quan Liu, Can Cui +10
Panoramic image segmentation in computational pathology presents a remarkable challenge due to the morphologically complex and variably scaled anatomy. For instance, the intricate…
mTREE: Multi-Level Text-Guided Representation End-to-End Learning for Whole Slide Image Analysis
Quan Liu, Ruining Deng, Can Cui +4
Multi-modal learning adeptly integrates visual and textual data, but its application to histopathology image and text analysis remains challenging, particularly with large, high-re…
PrPSeg: Universal Proposition Learning for Panoramic Renal Pathology Segmentation
Ruining Deng, Quan Liu, Can Cui +11
Understanding the anatomy of renal pathology is crucial for advancing disease diagnostics, treatment evaluation, and clinical research. The complex kidney system comprises various…
Nucleus subtype classification using inter-modality learning
Lucas W. Remedios, Shunxing Bao, Samuel W. Remedios +14
Understanding the way cells communicate, co-locate, and interrelate is essential to understanding human physiology. Hematoxylin and eosin (H&E) staining is ubiquitously available b…