no code implementations • 17 Oct 2024 • Shiao Xie, Hongyi Wang, Ziwei Niu, Hao Sun, Shuyi Ouyang, Yen-Wei Chen, Lanfen Lin
Semi-supervised learning (SSL) for medical image segmentation is a challenging yet highly practical task, which reduces reliance on large-scale labeled dataset by leveraging unlabeled samples.
1 code implementation • 23 Sep 2024 • Hongyi Wang, Xiuju Du, Jing Liu, Shuyi Ouyang, Yen-Wei Chen, Lanfen Lin
The advancement of Spatial Transcriptomics (ST) has facilitated the spatially-aware profiling of gene expressions based on histopathology images.
no code implementations • 8 Sep 2024 • Jiahua Dong, Yue Zhang, Qiuli Wang, Ruofeng Tong, Shihong Ying, Shaolin Gong, Xuanpu Zhang, Lanfen Lin, Yen-Wei Chen, S. Kevin Zhou
To achieve this, we devise a gaussian mixture model-based label filtering module that distinguishes noisy labels from clean labels.
no code implementations • 30 Aug 2024 • Shuyi Ouyang, Jinyang Zhang, Xiangye Lin, Xilai Wang, Qingqing Chen, Yen-Wei Chen, Lanfen Lin
We validated the performance of LSMS for MIRS and conventional medical image segmentation tasks across various datasets.
no code implementations • 6 Aug 2024 • Hao Sun, Yu Song, Jiaqing Liu, Jihong Hu, Yen-Wei Chen, Lanfen Lin
In this framework, all modalities and tasks are represented as unified tokens and trained using a single, consistent approach.
no code implementations • 23 Jul 2024 • Shuyi Ouyang, Hongyi Wang, Ziwei Niu, Zhenjia Bai, Shiao Xie, Yingying Xu, Ruofeng Tong, Yen-Wei Chen, Lanfen Lin
Moreover, given the potential variance in object size and appearance within a single image, attention to features of different scales can help to discover possible objects in the image.
1 code implementation • 7 Feb 2024 • Ziwei Niu, Shuyi Ouyang, Shiao Xie, Yen-Wei Chen, Lanfen Lin
Medical Image Analysis (MedIA) has emerged as a crucial tool in computer-aided diagnosis systems, particularly with the advancement of deep learning (DL) in recent years.
no code implementations • 26 Jan 2024 • Xinyao Yu, Hao Sun, Ziwei Niu, Rui Qin, Zhenjia Bai, Yen-Wei Chen, Lanfen Lin
We utilize temporal prompts on intermediate layers to imitate the acquiring stage, leverage similarity-based prompt interaction to imitate memory consolidation, and employ prompt generation strategy to imitate memory activation.
no code implementations • 19 Jan 2024 • Hongyi Wang, Xiuju Du, Jing Liu, Shuyi Ouyang, Yen-Wei Chen, Lanfen Lin
To address this limit, we propose M2ORT, a many-to-one regression Transformer that can accommodate the hierarchical structure of the pathology images through a decoupled multi-scale feature extractor.
no code implementations • CVPR 2024 • Huimin Huang, Yawen Huang, Lanfen Lin, Ruofeng Tong, Yen-Wei Chen, Hao Zheng, Yuexiang Li, Yefeng Zheng
Multi-task visual scene understanding aims to leverage the relationships among a set of correlated tasks which are solved simultaneously by embedding them within a uni- fied network.
2 code implementations • 2 Dec 2023 • Hongyi Wang, Luyang Luo, Fang Wang, Ruofeng Tong, Yen-Wei Chen, Hongjie Hu, Lanfen Lin, Hao Chen
Based on this idea, we design Iteratively Coupled Multiple Instance Learning (ICMIL) to couple the embedder and the bag classifier at a low cost.
1 code implementation • NeurIPS 2023 • Junkun Yuan, Xinyu Zhang, Hao Zhou, Jian Wang, Zhongwei Qiu, Zhiyin Shao, Shaofeng Zhang, Sifan Long, Kun Kuang, Kun Yao, Junyu Han, Errui Ding, Lanfen Lin, Fei Wu, Jingdong Wang
To further capture human characteristics, we propose a structure-invariant alignment loss that enforces different masked views, guided by the human part prior, to be closely aligned for the same image.
no code implementations • 14 Apr 2023 • Jiahua Dong, Guohua Cheng, Yue Zhang, Chengtao Peng, Yu Song, Ruofeng Tong, Lanfen Lin, Yen-Wei Chen
Multi-organ segmentation, which identifies and separates different organs in medical images, is a fundamental task in medical image analysis.
1 code implementation • 28 Mar 2023 • Hongyi Wang, Luyang Luo, Fang Wang, Ruofeng Tong, Yen-Wei Chen, Hongjie Hu, Lanfen Lin, Hao Chen
In ICMIL, we use category information in the bag-level classifier to guide the patch-level fine-tuning of the patch feature extractor.
no code implementations • CVPR 2023 • Huimin Huang, Shiao Xie, Lanfen Lin, Ruofeng Tong, Yen-Wei Chen, Yuexiang Li, Hong Wang, Yawen Huang, Yefeng Zheng
Semi-supervised learning improves data efficiency of deep models by leveraging unlabeled samples to alleviate the reliance on a large set of labeled samples.
1 code implementation • 26 Oct 2022 • Hongyi Wang, Lanfen Lin, Hongjie Hu, Qingqing Chen, Yinhao Li, Yutaro Iwamoto, Xian-Hua Han, Yen-Wei Chen, Ruofeng Tong
The framework contains two sub-tasks, of which semantic segmentation is the main task and super resolution is an auxiliary task aiding in rebuilding the high frequency information from the LR input.
no code implementations • 7 Aug 2022 • Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin
To escape from the dilemma between domain generalization and annotation costs, in this paper, we introduce a novel task named label-efficient domain generalization (LEDG) to enable model generalization with label-limited source domains.
1 code implementation • 29 Jul 2022 • Huimin Huang, Shiao Xie1, Lanfen Lin, Yutaro Iwamoto, Xianhua Han, Yen-Wei Chen, Ruofeng Tong
(2) A simple and effective spatial-aware inter-scale transformer is designed to interact among consensual regions in multiple scales, which can highlight the cross-scale dependency and resolve the complex scale variations.
1 code implementation • 28 Jul 2022 • Hao Sun, Hongyi Wang, Jiaqing Liu, Yen-Wei Chen, Lanfen Lin
Multimodal sentiment analysis and depression estimation are two important research topics that aim to predict human mental states using multimodal data.
no code implementations • 8 Mar 2022 • Yinao Li, Yutaro Iwamoto, Ryousuke Nakamura, Lanfen Lin, Ruofeng Tong, Yen-Wei Chen
Different from the texture transfer processing of RGB image, we use HR PAN images as the reference images and perform texture transfer for each frequency band of MS images, which is named 2. 5D texture transfer.
no code implementations • 27 Feb 2022 • Xu Ma, Junkun Yuan, Yen-Wei Chen, Ruofeng Tong, Lanfen Lin
To further boost model adaptation performance, we propose a novel method called Attention-based Cross-layer Domain Alignment (ACDA), which captures the semantic relationship between the source and target domains across model layers and calibrates each level of semantic information automatically through a dynamic attention mechanism.
1 code implementation • 8 Nov 2021 • Hongyi Wang, Shiao Xie, Lanfen Lin, Yutaro Iwamoto, Xian-Hua Han, Yen-Wei Chen, Ruofeng Tong
Therefore, Vision Transformers have emerged as alternative segmentation structures recently, for their innate ability of capturing long-range correlations through Self-Attention (SA).
1 code implementation • 13 Oct 2021 • Junkun Yuan, Xu Ma, Defang Chen, Fei Wu, Lanfen Lin, Kun Kuang
Domain generalization (DG) aims to learn from multiple known source domains a model that can generalize well to unknown target domains.
no code implementations • 4 Oct 2021 • Junkun Yuan, Xu Ma, Ruoxuan Xiong, Mingming Gong, Xiangyu Liu, Fei Wu, Lanfen Lin, Kun Kuang
Meanwhile, the existing of unobserved confounders which affect the input features and labels simultaneously cause spurious correlation and hinder the learning of the invariant relationship contained in the conditional distribution.
1 code implementation • 2 Oct 2021 • Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin
In this paper, we investigate a Single Labeled Domain Generalization (SLDG) task with only one source domain being labeled, which is more practical and challenging than the CDG task.
no code implementations • 2 Aug 2021 • Yue Zhang, Chengtao Peng, Liying Peng, Huimin Huang, Ruofeng Tong, Lanfen Lin, Jingsong Li, Yen-Wei Chen, Qingqing Chen, Hongjie Hu, Zhiyi Peng
In this work, we propose a novel LiTS method to adequately aggregate multi-phase information and refine uncertain region segmentation.
1 code implementation • 13 Jul 2021 • Junkun Yuan, Anpeng Wu, Kun Kuang, Bo Li, Runze Wu, Fei Wu, Lanfen Lin
We also learn confounder representations by encouraging them to be relevant to both the treatment and the outcome.
1 code implementation • 29 Apr 2021 • Panyanat Aonpong, Yutaro Iwamoto, Xian-Hua Han, Lanfen Lin, Yen-Wei Chen
The experiments demonstrated that the prediction accuracy can be improved significantly from 78. 61% (existing radiomics method) and 79. 14% (deep learning method) to 83. 28% by the proposed GGR.
no code implementations • 7 Mar 2021 • Huimin Huang, Ming Cai, Lanfen Lin, Jing Zheng, Xiongwei Mao, Xiaohan Qian, Zhiyi Peng, Jianying Zhou, Yutaro Iwamoto, Xian-Hua Han, Yen-Wei Chen, Ruofeng Tong
Our Graph- PGCR module is plug-and-play, which can be integrated into any architecture to improve its performance.
no code implementations • 27 Feb 2021 • Yingying Xu, Ming Cai, Lanfen Lin, Yue Zhang, Hongjie Hu, Zhiyi Peng, Qiaowei Zhang, Qingqing Chen, Xiongwei Mao, Yutaro Iwamoto, Xian-Hua Han, Yen-Wei Chen, Ruofeng Tong
In this paper, we propose a phase attention residual network (PA-ResSeg) to model multi-phase features for accurate liver tumor segmentation, in which a phase attention (PA) is newly proposed to additionally exploit the images of arterial (ART) phase to facilitate the segmentation of portal venous (PV) phase.
no code implementations • ICCV 2021 • Huimin Huang, Lanfen Lin, Yue Zhang, Yingying Xu, Jing Zheng, Xiongwei Mao, Xiaohan Qian, Zhiyi Peng, Jianying Zhou, Yen-Wei Chen, Ruofeng Tong
Semi-supervised learning (SSL) algorithms have attracted much attentions in medical image segmentation by leveraging unlabeled data, which challenge in acquiring massive pixel-wise annotated samples.
no code implementations • 16 Dec 2020 • Yuting Chen, Yanshi Wang, Yabo Ni, An-Xiang Zeng, Lanfen Lin
Finally, we employ a novel mutual unit to adaptively learn the similarity between various scenarios and incorporate it into multi-branch network.
Cultural Vocal Bursts Intensity Prediction
Recommendation Systems
no code implementations • 16 Oct 2020 • Yinhao Li, Yutaro Iwamoto, Lanfen Lin, Rui Xu, Yen-Wei Chen
We construct a parallel connection structure based on the group convolution and feature aggregation to build a 3D CNN that is as wide as possible with few parameters.
no code implementations • 27 Jun 2020 • Titinunt Kitrungrotsakul, Iwamoto Yutaro, Lanfen Lin, Ruofeng Tong, Jingsong Li, Yen-Wei Chen
Deep learning techniques have successfully been employed in numerous computer vision tasks including image segmentation.
6 code implementations • 19 Apr 2020 • Huimin Huang, Lanfen Lin, Ruofeng Tong, Hongjie Hu, Qiaowei Zhang, Yutaro Iwamoto, Xianhua Han, Yen-Wei Chen, Jian Wu
UNet, which is one of deep learning networks with an encoder-decoder architecture, is widely used in medical image segmentation.
Ranked #1 on
Medical Image Segmentation
on LiTS2017