6 citations · 32 across the 23 of their papers we have counts for
21 papers · 1 filter
NuNext: Reframing Nucleus Detection as Next-Point Detection
Zhongyi Shui, Honglin Li, Xiaozhong Ji +7
Nucleus detection in histopathology is pivotal for a wide range of clinical applications. Existing approaches either regress nuclear proxy maps that require complex post-processing…
CPathAgent: An Agent-based Foundation Model for Interpretable High-Resolution Pathology Image Analysis Mimicking Pathologists' Diagnostic Logic
Yuxuan Sun, Yixuan Si, Chenglu Zhu +5
Recent advances in computational pathology have led to the emergence of numerous foundation models. These models typically rely on general-purpose encoders with multi-instance lear…
PathVQ: Reforming Computational Pathology Foundation Model for Whole Slide Image Analysis via Vector Quantization
Honglin Li, Zhongyi Shui, Yunlong Zhang +2
Computational pathology and whole-slide image (WSI) analysis are pivotal in cancer diagnosis and prognosis. However, the ultra-high resolution of WSIs presents significant modeling…
Large-scale and Fine-grained Vision-language Pre-training for Enhanced CT Image Understanding
Zhongyi Shui, Jianpeng Zhang, Weiwei Cao +8
Artificial intelligence (AI) shows great potential in assisting radiologists to improve the efficiency and accuracy of medical image interpretation and diagnosis. However, a versat…
CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology
Yuxuan Sun, Yixuan Si, Chenglu Zhu +7
The emergence of large multimodal models (LMMs) has brought significant advancements to pathology. Previous research has primarily focused on separately training patch-level and wh…
Rethinking Transformer for Long Contextual Histopathology Whole Slide Image Analysis
Honglin Li, Yunlong Zhang, Pingyi Chen +3
Histopathology Whole Slide Image (WSI) analysis serves as the gold standard for clinical cancer diagnosis in the daily routines of doctors. To develop computer-aided diagnosis mode…
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…
PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration
Yuxuan Sun, Yunlong Zhang, Yixuan Si +7
Vision Language Models (VLMs) like CLIP have attracted substantial attention in pathology, serving as backbones for applications such as zero-shot image classification and Whole Sl…
AEM: Attention Entropy Maximization for Multiple Instance Learning based Whole Slide Image Classification
Yunlong Zhang, Honglin Li, Yunxuan Sun +4
Multiple Instance Learning (MIL) effectively analyzes whole slide images but faces overfitting due to attention over-concentration. While existing solutions rely on complex archite…
Test-Time Training for Semantic Segmentation with Output Contrastive Loss
Yunlong Zhang, Yuxuan Sun, Sunyi Zheng +3
Although deep learning-based segmentation models have achieved impressive performance on public benchmarks, generalizing well to unseen environments remains a major challenge. To i…
WsiCaption: Multiple Instance Generation of Pathology Reports for Gigapixel Whole-Slide Images
Pingyi Chen, Honglin Li, Chenglu Zhu +3
Whole slide images are the foundation of digital pathology for the diagnosis and treatment of carcinomas. Writing pathology reports is laborious and error-prone for inexperienced p…
Unleashing the Power of Prompt-driven Nucleus Instance Segmentation
Zhongyi Shui, Yunlong Zhang, Kai Yao +7
Nucleus instance segmentation in histology images is crucial for a broad spectrum of clinical applications. Current dominant algorithms rely on regression of nuclear proxy maps. Di…
Exploring Unsupervised Cell Recognition with Prior Self-activation Maps
Pingyi Chen, Chenglu Zhu, Zhongyi Shui +4
The success of supervised deep learning models on cell recognition tasks relies on detailed annotations. Many previous works have managed to reduce the dependency on labels. Howeve…
Masked conditional variational autoencoders for chromosome straightening
Jingxiong Li, Sunyi Zheng, Zhongyi Shui +9
Karyotyping is of importance for detecting chromosomal aberrations in human disease. However, chromosomes easily appear curved in microscopic images, which prevents cytogeneticists…
Semi-supervised Cell Recognition under Point Supervision
Zhongyi Shui, Yizhi Zhao, Sunyi Zheng +6
Cell recognition is a fundamental task in digital histopathology image analysis. Point-based cell recognition (PCR) methods normally require a vast number of annotations, which is…
PathAsst: A Generative Foundation AI Assistant Towards Artificial General Intelligence of Pathology
Yuxuan Sun, Chenglu Zhu, Sunyi Zheng +6
As advances in large language models (LLMs) and multimodal techniques continue to mature, the development of general-purpose multimodal large language models (MLLMs) has surged, of…
Task-specific Fine-tuning via Variational Information Bottleneck for Weakly-supervised Pathology Whole Slide Image Classification
Honglin Li, Chenglu Zhu, Yunlong Zhang +5
While Multiple Instance Learning (MIL) has shown promising results in digital Pathology Whole Slide Image (WSI) classification, such a paradigm still faces performance and generali…
DPA-P2PNet: Deformable Proposal-aware P2PNet for Accurate Point-based Cell Detection
Zhongyi Shui, Sunyi Zheng, Chenglu Zhu +6
Point-based cell detection (PCD), which pursues high-performance cell sensing under low-cost data annotation, has garnered increased attention in computational pathology community.…
Unsupervised Dense Nuclei Detection and Segmentation with Prior Self-activation Map For Histology Images
Pingyi Chen, Chenglu Zhu, Zhongyi Shui +4
The success of supervised deep learning models in medical image segmentation relies on detailed annotations. However, labor-intensive manual labeling is costly and inefficient, esp…
End-to-end cell recognition by point annotation
Zhongyi Shui, Shichuan Zhang, Chenglu Zhu +4
Reliable quantitative analysis of immunohistochemical staining images requires accurate and robust cell detection and classification. Recent weakly-supervised methods usually estim…
ChrSNet: Chromosome Straightening using Self-attention Guided Networks
Sunyi Zheng, Jingxiong Li, Zhongyi Shui +4
Karyotyping is an important procedure to assess the possible existence of chromosomal abnormalities. However, because of the non-rigid nature, chromosomes are usually heavily curve…