Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement

Yanyan Huang, Weiqin Zhao, Yihang Chen, Yu Fu, Lequan Yu.

Conference on Neural Information Processing Systems (NeurIPS), 2024

We introduce a novel approach for efficient task-specific adaptation in pathology foundation models. Our method leverages concept-guided feature enhancement to achieve superior performance while maintaining computational efficiency. The framework demonstrates significant improvements across various pathology analysis tasks.

Unleash the Power of State Space Model for Whole Slide Image with Local Aware Scanning and Importance Resampling

Yanyan Huang, Weiqin Zhao, Yu Fu, Lingting Zhu, and Lequan Yu.

IEEE Transactions on Medical Imaging (TMI), 2024

This paper introduces a new Pathology Mamba (PAM) for more accurate and robust WSI analysis. It includes three carefully designed components to tackle the challenges of enormous image size, the utilization of local and hierarchical information, and the mismatch between the feature distributions of training and testing during WSI analysis.

ConSlide: Asynchronous Hierarchical Interaction Transformer with Breakup-Reorganize Rehearsal for Continual Whole Slide Image Analy

Yanyan Huang, Weiqin Zhao, Shujun Wang, Yu Fu, Yuming Jiang, Lequan Yu.

International Conference on Computer Vision (ICCV), poster, 2023

Propose the first continual learning framework for WSI analysis, named ConSlide, to tackle the challenges of enormous image size, utilization of hierarchical structure, and catastrophic forgetting by progressive model updating on multiple sequential datasets.

OTFPF: Optimal Transport Based Feature Pyramid Fusion Network for Brain Age Estimation

Yu Fu$^{*}$, Yanyan Huang$^{*}$, Zhe Zhang, Shunjie Dong, Le Xue, Meng Niu, Yunxin Li, Zhiguo Shi, Yalin Wang, Hong Zhang, Mei Tian, Cheng Zhuo.

Information Fusion (IF), 2023

Propose the Optimal Transport based Feature Pyramid Fusion (OTFPF) network for estimating brain age using T1 MRIs. Experimental results utilizing a dataset of 12,909 MRIs from individuals aged 3–97 years demonstrate the accurate estimation of brain age by the OTFPF network.

HDNet: Hierarchical Dynamic Network for Gait Recognition using Millimeter-Wave Radar

Yanyan Huang, Yong Wang, Kun Shi, Chaojie Gu, Yu Fu, Cheng Zhuo, Zhiguo Shi.

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), poster, 2023

Propose point flow as a novel point clouds descriptor to explore more dynamic information for human gait. Devise a dynamic frame sampling module to promote the efficiency of computation without deteriorating performance noticeably.

Active Index: An Integrated Index To Reveal Disrupted Brain Network Organizations Of Major Depressive Disorder Patients

Yu Fu$^{*}$, Yanyan Huang$^{*}$, Meng Niu, Le Xue, Shunjie Dong, Shunlin Guo, Junqiang Lei, Cheng Zhuo.

IEEE International Symposium on Biomedical Imaging (ISBI), poster, 2022

For the first time discussed the differences between MDD and HC using both rich club and diverse club metrics and found the complementarity of them in analyzing brain networks. Proposed “active index”, which defines a group of nodes that tend to be diversely distributed across communities while avoiding being a hub of a community.