152 citations · 188 across the 9 of their papers we have counts for
9 papers
Cross-modality Attention Adapter: A Glioma Segmentation Fine-tuning Method for SAM Using Multimodal Brain MR Images
Xiaoyu Shi, Shurong Chai, Yinhao Li +4
According to the 2021 World Health Organization (WHO) Classification scheme for gliomas, glioma segmentation is a very important basis for diagnosis and genotype prediction. In gen…
Ladder Fine-tuning approach for SAM integrating complementary network
Shurong Chai, Rahul Kumar Jain, Shiyu Teng +4
Recently, foundation models have been introduced demonstrating various tasks in the field of computer vision. These models such as Segment Anything Model (SAM) are generalized mode…
Tailored Multi-Organ Segmentation with Model Adaptation and Ensemble
Jiahua Dong, Guohua Cheng, Yue Zhang +5
Multi-organ segmentation, which identifies and separates different organs in medical images, is a fundamental task in medical image analysis. Recently, the immense success of deep…
Iteratively Coupled Multiple Instance Learning from Instance to Bag Classifier for Whole Slide Image Classification
Hongyi Wang, Luyang Luo, Fang Wang +5
Whole Slide Image (WSI) classification remains a challenge due to their extremely high resolution and the absence of fine-grained labels. Presently, WSI classification is usually r…
Super-Resolution Based Patch-Free 3D Image Segmentation with High-Frequency Guidance
Hongyi Wang, Lanfen Lin, Hongjie Hu +6
High resolution (HR) 3D images are widely used nowadays, such as medical images like Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). However, segmentation of these 3…
ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation
Huimin Huang, Shiao Xie1, Lanfen Lin +4
Recently, a variety of vision transformers have been developed as their capability of modeling long-range dependency. In current transformer-based backbones for medical image segme…
CubeMLP: An MLP-based Model for Multimodal Sentiment Analysis and Depression Estimation
Hao Sun, Hongyi Wang, Jiaqing Liu +2
Multimodal sentiment analysis and depression estimation are two important research topics that aim to predict human mental states using multimodal data. Previous research has focus…
Efficient and Accurate Hyperspectral Pansharpening Using 3D VolumeNet and 2.5D Texture Transfer
Yinao Li, Yutaro Iwamoto, Ryousuke Nakamura +3
Recently, convolutional neural networks (CNN) have obtained promising results in single-image SR for hyperspectral pansharpening. However, enhancing CNNs' representation ability wi…
Attention-based Cross-Layer Domain Alignment for Unsupervised Domain Adaptation
Xu Ma, Junkun Yuan, Yen-wei Chen +2
Unsupervised domain adaptation (UDA) aims to learn transferable knowledge from a labeled source domain and adapts a trained model to an unlabeled target domain. To bridge the gap b…