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3D Shuffle-Mixer: An Efficient Context-Aware Vision Learner of Transformer-MLP Paradigm for Dense Prediction in Medical Volume [article]

Jianye Pang, Cheng Jiang, Yihao Chen, Jianbo Chang, Ming Feng, Renzhi Wang, Jianhua Yao
2022 arXiv   pre-print
volume context in a slice-aware manner, and a MLP view aggregator is employed to project the learned full-view rich context to the volume feature in a view-aware manner.  ...  Dense prediction in medical volume provides enriched guidance for clinical analysis. CNN backbones have met bottleneck due to lack of long-range dependencies and global context modeling power.  ...  Synapse Multi-organ Segmentation in CT Images: We present the performance upon synapse multi-organ CT segmentation task in Table II .  ... 
arXiv:2204.06779v1 fatcat:txccldfcdfesjetd4f7vxzskqq

TransAttUnet: Multi-level Attention-guided U-Net with Transformer for Medical Image Segmentation [article]

Bingzhi Chen, Yishu Liu, Zheng Zhang, Guangming Lu, Adams Wai Kin Kong
2022 arXiv   pre-print
Inspired by Transformer, the self-aware attention (SAA) module with Transformer Self Attention (TSA) and Global Spatial Attention (GSA) is incorporated into TransAttUnet to effectively learn the non-local  ...  Accurate segmentation of organs or lesions from medical images is crucial for reliable diagnosis of diseases and organ morphometry.  ...  Self-aware Attention Module Firstly, the proposed TransAttUnet augments the standard U-Net with a robust and effective self-aware attention module, that is positioned at the bottom of U-shaped architecture  ... 
arXiv:2107.05274v2 fatcat:nxcduoxf25fp5ce26ow477llbq

Orientation and Context Entangled Network for Retinal Vessel Segmentation [article]

Xinxu Wei, Kaifu Yang, Danilo Bzdok, Yongjie Li
2022 arXiv   pre-print
To achieve complex orientation aware, a Dynamic Complex Orientation Aware Convolution (DCOA Conv) is proposed to extract complex vessels with multiple orientations for improving the vessel continuity.  ...  Most of the existing deep learning based methods for vessel segmentation neglect two important aspects of retinal vessels, one is the orientation information of vessels, and the other is the contextual  ...  The remaining parts of this paper are organized as follows. In Section 2, we describe some related works on vessel segmentation, self-attention mechanism and convolutional operators.  ... 
arXiv:2207.11396v1 fatcat:vtejftmxhvfxlh2umbl7exl5fy

Decoupled Multi-task Learning with Cyclical Self-Regulation for Face Parsing [article]

Qingping Zheng, Jiankang Deng, Zheng Zhu, Ying Li, Stefanos Zafeiriou
2022 arXiv   pre-print
To tackle these problems, we propose a novel Decoupled Multi-task Learning with Cyclical Self-Regulation (DML-CSR) for face parsing.  ...  model then is used to self-distill subsequent models, through alternating iterations.  ...  Different from the binary boundary attention loss proposed in [21] , we further introduce category-aware boundary-attention semantic loss, significantly improving segmentation results of underrepresented  ... 
arXiv:2203.14448v1 fatcat:vyxjnmwranhwtprarxvj2haiui

Efficient Context-Aware Network for Abdominal Multi-organ Segmentation [article]

Fan Zhang, Yu Wang, Hua Yang
2021 arXiv   pre-print
In order to make full use of the overall 3D context, we develop a whole-volume-based coarse-to-fine framework for efficient and effective abdominal multi-organ segmentation.  ...  For the context block, we propose strip pooling module to capture anisotropic and long-range contextual information, which exists in abdominal scene.  ...  Acknowledgment We sincerely appreciate the organizers with the donation of FLARE2021 dataset. We declare that pre-trained models and additional datasets are not used in this paper.  ... 
arXiv:2109.10601v4 fatcat:b4ow46iz6je57kdhoscql4t3me

Boundary-Aware Transformers for Skin Lesion Segmentation [chapter]

Jiacheng Wang, Lan Wei, Liansheng Wang, Qichao Zhou, Lei Zhu, Jing Qin
2021 Lecture Notes in Computer Science  
Recently, transformers have been proposed as a promising tool for global context modeling by employing a powerful global attention mechanism, but one of their main shortcomings when applied to segmentation  ...  We propose a novel boundary-aware transformer (BAT) to comprehensively address the challenges of automatic skin lesion segmentation.  ...  For example, TransUNet [6] , a hybrid architecture of CNN and transformer, performs well on Synapse multi-organ segmentation.  ... 
doi:10.1007/978-3-030-87193-2_20 fatcat:ya2h3civnbfhzdfvdrnov2oavi

MISSU: 3D Medical Image Segmentation via Self-distilling TransUNet [article]

Nan Wang, Shaohui Lin, Xiaoxiao Li, Ke Li, Yunhang Shen, Yue Gao, Lizhuang Ma
2022 arXiv   pre-print
To this end, we propose to self-distill a Transformer-based UNet for medical image segmentation, which simultaneously learns global semantic information and local spatial-detailed features.  ...  This motivates us to design the efficiently Transformer-based UNet model and study the feasibility of Transformer-based network architectures for medical image segmentation tasks.  ...  This arouses our rethinking: how to design a unified framework for segmentation that implicitly models global semantic contexts and local spatial-detailed information during training while being efficient  ... 
arXiv:2206.00902v1 fatcat:earitthqrvgntoxmunjvlj22mi

Transformers in Medical Image Analysis: A Review [article]

Kelei He, Chen Gan, Zhuoyuan Li, Islem Rekik, Zihao Yin, Wen Ji, Yang Gao, Qian Wang, Junfeng Zhang, Dinggang Shen
2022 arXiv   pre-print
Our paper aims to promote awareness and application of Transformers in the field of medical image analysis.  ...  Second, we review various Transformer architectures tailored for medical image applications and discuss their limitations.  ...  [202] proposed a context-aware network called CA-Net for semi-supervised LA segmentation from 3D MRI.  ... 
arXiv:2202.12165v2 fatcat:wjeuwhcu5ngybcia5k7lyxntgi

Class-Aware Generative Adversarial Transformers for Medical Image Segmentation [article]

Chenyu You, Ruihan Zhao, Fenglin Liu, Siyuan Dong, Sandeep Chinchali, Ufuk Topcu, Lawrence Staib, James S. Duncan
2022 arXiv   pre-print
In this work, we present CASTformer, a novel type of generative adversarial transformers, for 2D medical image segmentation.  ...  semantic contexts and anatomical textures.  ...  With the aid of feature maps of different resolutions, our model is capable of modeling multi-resolution spatially local contexts. Hierarchical Feature Representation.  ... 
arXiv:2201.10737v3 fatcat:opygzwskbngtxkxza7ppend4he

Semantic-Aware Contrastive Learning for Multi-object Medical Image Segmentation [article]

Ho Hin Lee, Yucheng Tang, Qi Yang, Xin Yu, Shunxing Bao, Leon Y. Cai, Lucas W. Remedios, Bennett A. Landman, Yuankai Huo
2021 arXiv   pre-print
In this paper, we propose a simple semantic-aware contrastive learning approach leveraging attention masks to advance multi-object semantic segmentation.  ...  We evaluate our proposed method on a multi-organ medical image segmentation task with both in-house data and MICCAI Challenge 2015 BTCV datasets.  ...  In this work, we propose a novel semantic-aware contrastive framework that extends self-supervised contrastive loss and integrates attention guidance from coarse segmentation.  ... 
arXiv:2106.01596v2 fatcat:cm7xh4qrarewjj5gegpudldzve

Pseudo-Label Guided Multi-Contrast Generalization for Non-Contrast Organ-Aware Segmentation [article]

Ho Hin Lee, Yucheng Tang, Riqiang Gao, Qi Yang, Xin Yu, Shunxing Bao, James G. Terry, J. Jeffrey Carr, Yuankai Huo, Bennett A. Landman
2022 arXiv   pre-print
8.00% (external aorta annotated) for abdominal organs segmentation.  ...  We validate our approach on multi-organ segmentation with paired non-contrast & contrast-enhanced CT scans using five-fold cross-validation.  ...  Twelve transformer blocks are used, comprising of multi-head self-attention modules and multilayer perceptron sublayers.  ... 
arXiv:2205.05898v1 fatcat:zmamp2qf4rdrrcg7fyhbbn4r3i

ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation [article]

Huimin Huang, Shiao Xie1, Lanfen Lin, Yutaro Iwamoto, Xianhua Han, Yen-Wei Chen, Ruofeng Tong
2022 arXiv   pre-print
In current transformer-based backbones for medical image segmentation, convolutional layers were replaced with pure transformers, or transformers were added to the deepest encoder to learn global context  ...  local features with the transformer-based global cues in each scale, where the row-wise and column-wise global dependencies can be extracted by a lightweight Dual-Axis MSA. (2) A simple and effective spatial-aware  ...  The Multi-Organ Nucleus Segmentation Challenge [Kumar et al., 2017] contains 30 images for training, and 14 images for testing.  ... 
arXiv:2207.14552v1 fatcat:phj246ffnnbhzj6jalhb2cu5la

Boundary-Aware Refined Network for Automatic Building Extraction in Very High-Resolution Urban Aerial Images

Yuwei Jin, Wenbo Xu, Ce Zhang, Xin Luo, Haitao Jia
2021 Remote Sensing  
The unique properties of the proposed BARNet are the gated-attention refined fusion unit, the denser atrous spatial pyramid pooling module, and the boundary-aware loss.  ...  segmentation for large-scale buildings and result in predictions with huge uncertainty at building boundaries.  ...  Acknowledgments: The authors thank Wuhan University and ISPRS for providing the open-access and free aerial image dataset.  ... 
doi:10.3390/rs13040692 fatcat:egqqzgboxzclln3zeui66i77o4

SimulLR: Simultaneous Lip Reading Transducer with Attention-Guided Adaptive Memory [article]

Zhijie Lin, Zhou Zhao, Haoyuan Li, Jinglin Liu, Meng Zhang, Xingshan Zeng, Xiaofei He
2021 arXiv   pre-print
Therefore, we devise a novel attention-guided adaptive memory to organize semantic information of history segments and enhance the visual representations with acceptable computation-aware latency.  ...  encoder, we construct a truncated 3D convolution and time-restricted self-attention layer to perform the frame-to-frame interaction within a video segment containing fixed number of frames. (3) The history  ...  For both the segment sequence encoder and language model, we stack four self-attention layers with feed-forward network.  ... 
arXiv:2108.13630v1 fatcat:mvhi6fatanekfp4oqe52qphzyu

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, TIP 2020 2795-2807 A Multi-Scale Spatial-Temporal Attention Model for Person Re-Identifica- tion in Videos.  ...  ., +, TIP 2020 7192-7202 One-Pass Multi-Task Networks With Cross-Task Guided Attention for Brain Tumor Segmentation.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m
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