activity
20242026
collaborators

12 papers

cs.CV2026

SCR2-ST: Combine Single Cell with Spatial Transcriptomics for Efficient Active Sampling via Reinforcement Learning

Junchao Zhu, Ruining Deng, Junlin Guo +13

Spatial transcriptomics (ST) is an emerging technology that enables researchers to investigate the molecular relationships underlying tissue morphology. However, acquiring ST data…

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…

cs.CV2025

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…

q-bio.QM2025

Evaluating New AI Cell Foundation Models on Challenging Kidney Pathology Cases Unaddressed by Previous Foundation Models

Runchen Wang, Junlin Guo, Siqi Lu +12

Accurate cell nuclei segmentation is critical for downstream tasks in kidney pathology and remains a major challenge due to the morphological diversity and imaging variability of r…

cs.CV2025

GloFinder: AI-empowered QuPath Plugin for WSI-level Glomerular Detection, Visualization, and Curation

Jialin Yue, Tianyuan Yao, Ruining Deng +7

Artificial intelligence (AI) has demonstrated significant success in automating the detection of glomeruli, the key functional units of the kidney, from whole slide images (WSIs) i…

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…