56 citations · 94 across the 8 of their papers we have counts for
9 papers
Team Westwood Solution for MIDOG 2025 Challenge: An Ensemble-CNN-Based Approach For Mitosis Detection And Classification
Tengyou Xu, Haochen Yang, Xiang 'Anthony' Chen +2
This abstract presents our solution (Team Westwood) for mitosis detection and atypical mitosis classification in the MItosis DOmain Generalization (MIDOG) 2025 challenge. For mitos…
Z-Stack Scanning can Improve AI Detection of Mitosis: A Case Study of Meningiomas
Hongyan Gu, Ellie Onstott, Wenzhong Yan +5
Z-stack scanning is an emerging whole slide imaging technology that captures multiple focal planes alongside the z-axis of a glass slide. Because z-stacking can offer enhanced dept…
Supporting Mitosis Detection AI Training with Inter-Observer Eye-Gaze Consistencies
Hongyan Gu, Zihan Yan, Ayesha Alvi +6
The expansion of artificial intelligence (AI) in pathology tasks has intensified the demand for doctors' annotations in AI development. However, collecting high-quality annotations…
Majority Voting of Doctors Improves Appropriateness of AI Reliance in Pathology
Hongyan Gu, Chunxu Yang, Shino Magaki +17
As Artificial Intelligence (AI) making advancements in medical decision-making, there is a growing need to ensure doctors develop appropriate reliance on AI to avoid adverse outcom…
Domain generalization across tumor types, laboratories, and species -- insights from the 2022 edition of the Mitosis Domain Generalization Challenge
Marc Aubreville, Nikolas Stathonikos, Taryn A. Donovan +27
Recognition of mitotic figures in histologic tumor specimens is highly relevant to patient outcome assessment. This task is challenging for algorithms and human experts alike, with…
Augmenting Pathologists with NaviPath: Design and Evaluation of a Human-AI Collaborative Navigation System
Hongyan Gu, Chunxu Yang, Mohammad Haeri +7
Artificial Intelligence (AI) brings advancements to support pathologists in navigating high-resolution tumor images to search for pathology patterns of interest. However, existing…
Detecting Mitoses with a Convolutional Neural Network for MIDOG 2022 Challenge
Hongyan Gu, Mohammad Haeri, Shuo Ni +4
This work presents a mitosis detection method with only one vanilla Convolutional Neural Network (CNN). Our method consists of two steps: given an image, we first apply a CNN using…
Lessons Learned from Designing an AI-Enabled Diagnosis Tool for Pathologists
Hongyan Gu, Jingbin Huang, Lauren Hung +1
Despite the promises of data-driven artificial intelligence (AI), little is known about how we can bridge the gulf between traditional physician-driven diagnosis and a plausible fu…
Improving Workflow Integration with xPath: Design and Evaluation of a Human-AI Diagnosis System in Pathology
Hongyan Gu, Yuan Liang, Yifan Xu +12
Recent developments in AI have provided assisting tools to support pathologists' diagnoses. However, it remains challenging to incorporate such tools into pathologists' practice; o…