Search Results for author: Anjia Han

Found 8 papers, 3 papers with code

Dynamic Hypergraph Representation for Bone Metastasis Cancer Analysis

no code implementations28 Jan 2025 Yuxuan Chen, Jiawen Li, Huijuan Shi, Yang Xu, Tian Guan, Lianghui Zhu, Yonghong He, Anjia Han

A low-rank strategy is used to reduce the complexity of parameters in learning hypergraph structures, while a Gumbel-Softmax-based sampling strategy optimizes the patch distribution across hyperedges.

Multiple Instance Learning whole slide images

Diagnostic Text-guided Representation Learning in Hierarchical Classification for Pathological Whole Slide Image

no code implementations16 Nov 2024 Jiawen Li, Qiehe Sun, Renao Yan, Yizhi Wang, Yuqiu Fu, Yani Wei, Tian Guan, Huijuan Shi, Yonghonghe He, Anjia Han

With the development of digital imaging in medical microscopy, artificial intelligent-based analysis of pathological whole slide images (WSIs) provides a powerful tool for cancer diagnosis.

Classification Image Classification +3

Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation

1 code implementation26 Jul 2024 Jiabo Ma, Zhengrui Guo, Fengtao Zhou, Yihui Wang, Yingxue Xu, Yu Cai, Zhengjie ZHU, Cheng Jin, Yi Lin, Xinrui Jiang, Anjia Han, Li Liang, Ronald Cheong Kin Chan, Jiguang Wang, Kwang-Ting Cheng, Hao Chen

To address this gap, we established a most comprehensive benchmark to evaluate the performance of off-the-shelf foundation models across six distinct clinical task types, encompassing a total of 39 specific tasks.

Representation Learning Self-Knowledge Distillation

A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model

no code implementations22 Jul 2024 Yingxue Xu, Yihui Wang, Fengtao Zhou, Jiabo Ma, Shu Yang, Huangjing Lin, Xin Wang, Jiguang Wang, Li Liang, Anjia Han, Ronald Cheong Kin Chan, Hao Chen

To our knowledge, this is the first attempt to incorporate multimodal knowledge at the slide level for enhancing pathology FMs, expanding the modelling context from unimodal to multimodal knowledge and from patch-level to slide-level.

whole slide images

Leveraging Pre-trained Models for FF-to-FFPE Histopathological Image Translation

1 code implementation26 Jun 2024 Qilai Zhang, Jiawen Li, Peiran Liao, Jiali Hu, Tian Guan, Anjia Han, Yonghong He

Our task is to translate FF images into FFPE style, thereby improving the image quality for diagnostic purposes.

Language Modelling Translation

Deep Semi-supervised Metric Learning with Dual Alignment for Cervical Cancer Cell Detection

no code implementations7 Apr 2021 Zhizhong Chai, Luyang Luo, Huangjing Lin, Hao Chen, Anjia Han, Pheng-Ann Heng

Specifically, our model learns a metric space and conducts dual alignment of semantic features on both the proposal level and the prototype levels.

Cell Detection Metric Learning +2

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