collaborators

7 papers

cs.CV2025

Fine-grained Multi-class Nuclei Segmentation with Molecular-empowered All-in-SAM Model

Xueyuan Li, Can Cui, Ruining Deng +7

Purpose: Recent developments in computational pathology have been driven by advances in Vision Foundation Models, particularly the Segment Anything Model (SAM). This model facilita…

cs.CV2025

ZeroReg3D: A Zero-shot Registration Pipeline for 3D Consecutive Histopathology Image Reconstruction

Juming Xiong, Ruining Deng, Jialin Yue +10

Histological analysis plays a crucial role in understanding tissue structure and pathology. While recent advancements in registration methods have improved 2D histological analysis…

eess.IV2025

Quantitative Benchmarking of Anomaly Detection Methods in Digital Pathology

Can Cui, Xindong Zheng, Ruining Deng +8

Anomaly detection has been widely studied in the context of industrial defect inspection, with numerous methods developed to tackle a range of challenges. In digital pathology, ano…

eess.IV2025

IRS: Incremental Relationship-guided Segmentation for Digital Pathology

Ruining Deng, Junchao Zhu, Juming Xiong +14

Continual learning is rapidly emerging as a key focus in computer vision, aiming to develop AI systems capable of continuous improvement, thereby enhancing their value and practica…

cs.CV2025

DeepAndes: A Self-Supervised Vision Foundation Model for Multi-Spectral Remote Sensing Imagery of the Andes

Junlin Guo, James R. Zimmer-Dauphinee, Jordan M. Nieusma +16

By mapping sites at large scales using remotely sensed data, archaeologists can generate unique insights into long-term demographic trends, inter-regional social networks, and past…

eess.IV2024

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…