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FreMIM: Fourier Transform Meets Masked Image Modeling for Medical Image Segmentation [article]

Wenxuan Wang, Jing Wang, Chen Chen, Jianbo Jiao, Yuanxiu Cai, Shanshan Song, Jiangyun Li
2023 arXiv   pre-print

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2023 pre-print arXiv:2304.10864v1 fatcat:cadhfar6wzf45dzzf33nqlrlcu

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2023 pre-print
arXiv:2304.10864v2 fatcat:ttpugd3e6nftzovhqgkq4fdz4e
named FreMIM for self-supervised pre-training to better accomplish medical image segmentation tasks.  ...  multi-stage supervision to guide the representation learning during the pre-training phase.  ...  For medical images with various modalities, the Fourier Transform is operated on each channel independently.  ... 
arXiv:2304.10864v3 fatcat:vuf7j3c36fftxltqlcenkoexfe
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Citation

Wenxuan Wang, Jing Wang, Chen Chen, Jianbo Jiao, Yuanxiu Cai, Shanshan Song, Jiangyun Li. "FreMIM: Fourier Transform Meets Masked Image Modeling for Medical Image Segmentation." arXiv (2023)

Multiscale Progressive Text Prompt Network for Medical Image Segmentation [article]

Xianjun Han, Qianqian Chen, Zhaoyang Xie, Xuejun Li, Hongyu Yang
2023 arXiv   pre-print

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https://web.archive.org/web/20230803095916/https://arxiv.org/pdf/2307.00174v1.pdf

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The accurate segmentation of medical images is a crucial step in obtaining reliable morphological statistics.  ...  In the second stage, medical image and text prior prompts are sent into the PPE inherited from the first stage to achieve the downstream medical image segmentation task.  ...  To better merge information from different distances, a variety of hybrid CNN-Transformer structures were used to encode global features with Transformer while retaining the CNN's ability to extract local  ... 
arXiv:2307.00174v1 fatcat:3n7akp6arzbzdghksvukhde3sm
Citation

Xianjun Han, Qianqian Chen, Zhaoyang Xie, Xuejun Li, Hongyu Yang. "Multiscale Progressive Text Prompt Network for Medical Image Segmentation." arXiv (2023)

TEC-Net: Vision Transformer Embrace Convolutional Neural Networks for Medical Image Segmentation [article]

Rui Sun, Tao Lei, Weichuan Zhang, Yong Wan, Yong Xia, Asoke K. Nandi
2023 arXiv   pre-print

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2023 pre-print arXiv:2306.04086v2 fatcat:dc5p4a3x4bdm3arwpyqrvbsky4

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2023 pre-print
arXiv:2306.04086v1 fatcat:iumignto5fe4jhu6tlkjltffaa
self-attention leading to low segmentation accuracy for medical images with complex backgrounds.  ...  Second, although the Transformer branch can model the global information of images, the conventional self-attention only focuses on the spatial self-attention of images and ignores the channel and cross-dimensional  ...  During this process, the information exchange and fusion between CNN and Transformer branches play an important role in the accurate segmentation of target regions.  ... 
arXiv:2306.04086v3 fatcat:jafouz54anes5pyyq7jttec2iu
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Rui Sun, Tao Lei, Weichuan Zhang, Yong Wan, Yong Xia, Asoke K. Nandi. "TEC-Net: Vision Transformer Embrace Convolutional Neural Networks for Medical Image Segmentation." arXiv (2023)

Deep Learning Attention Mechanism in Medical Image Analysis: Basics and Beyonds

Xiang Li, Minglei Li, Pengfei Yan, Guanyi Li, Yuchen Jiang, Hao Luo, Shen Yin
2023 International Journal of Network Dynamics and Intelligence  

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For its application in medical image analysis, we summarize the related methods in medical image classification, segmentation, detection, and enhancement.  ...  At present, the method of deep learning technology combined with attention mechanism is a research hotspot and has achieved state-of-the-art results in many medical image tasks.  ...  Multi-scale guided attention network for medical image segmentation proposed by Sinha et al.  ... 
doi:10.53941/ijndi0201006 fatcat:tsaaxws5fvfmxhlcmhi7hu6pwi
Open Access
Citation

Xiang Li, Minglei Li, Pengfei Yan, Guanyi Li, Yuchen Jiang, Hao Luo, Shen Yin. "Deep Learning Attention Mechanism in Medical Image Analysis: Basics and Beyonds." International Journal of Network Dynamics and Intelligence (2023) 93-116

FusionU-Net: U-Net with Enhanced Skip Connection for Pathology Image Segmentation [article]

Zongyi Li, Hongbing Lyu, Jun Wang
2023 arXiv   pre-print

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In recent years, U-Net and its variants have been widely used in pathology image segmentation tasks.  ...  To address this issue, we propose a new segmentation network called FusionU-Net, which is based on U-Net structure and incorporates a fusion module to exchange information between different skip connections  ...  Introduction Medical imaging segmentation is a crucial area of AI research with great application value in areas such as computer aided diagnosis [1] and image-guided surgery [2] One of main chanllenges  ... 
arXiv:2310.10951v1 fatcat:v25axc4sf5aipmgirkx57omcee
Citation

Zongyi Li, Hongbing Lyu, Jun Wang. "FusionU-Net: U-Net with Enhanced Skip Connection for Pathology Image Segmentation." arXiv (2023)

Multi-Scale Cross Contrastive Learning for Semi-Supervised Medical Image Segmentation [article]

Qianying Liu, Xiao Gu, Paul Henderson, Fani Deligianni
2023 arXiv   pre-print

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Semi-supervised learning has demonstrated great potential in medical image segmentation by utilizing knowledge from unlabeled data.  ...  images.  ...  classimbalanced medical imaging segmentation datasets [20] .  ... 
arXiv:2306.14293v1 fatcat:il2y3oa2abgmzitqh6not4sm4a
Citation

Qianying Liu, Xiao Gu, Paul Henderson, Fani Deligianni. "Multi-Scale Cross Contrastive Learning for Semi-Supervised Medical Image Segmentation." arXiv (2023)

Deep automatic segmentation of brain tumours in interventional ultrasound data

Ramy A. Zeineldin, Alex Pollok, Tim Mangliers, Mohamed E. Karar, Franziska Mathis-Ullrich, Oliver Burgert
2022 Current Directions in Biomedical Engineering  

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The outcomes show that using a transformer with UNet is advantageous providing an efficient segmentation modelling long-range dependencies between each iUS image.  ...  In particular, the enhanced TransUNet was able to predict cavity segmentation in iUS data with an inference rate of more than 125 FPS.  ...  First, UNet [8] is used as the baseline CNN due to its impressive performance and popularity in medical image segmentation tasks.  ... 
doi:10.1515/cdbme-2022-0034 fatcat:p6u5k5ks4rbsjfcd4z35jatexi
DOAJ
Citation

Ramy A. Zeineldin, Alex Pollok, Tim Mangliers, Mohamed E. Karar, Franziska Mathis-Ullrich, Oliver Burgert. "Deep automatic segmentation of brain tumours in interventional ultrasound data." Current Directions in Biomedical Engineering 8.1 (2022) 133-137

Integrative analysis of T cell motility from multi-channel microscopy data using TIAM

Viveka Mayya, Willie Neiswanger, Ricardo Medina, Chris H. Wiggins, Michael L. Dustin
2015 JIM - Journal of Immunological Methods  

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The cells are detected by a hybrid approach involving edge detection and Hough transforms from transmitted light images.  ...  Cell positions are used to perform local segmentation for extracting features from transmitted light, reflection and fluorescence channels and associating them with cells and cell-tracks to facilitate  ...  Assistance of the Light Microscopy Core Facility at the NYU Medical Center is also acknowledged.  ... 
doi:10.1016/j.jim.2014.11.004 pmid:25445324 pmcid:PMC4323926 fatcat:cu7sefccs5dybegmxw2gpkolby
Open Access
Citation

Viveka Mayya, Willie Neiswanger, Ricardo Medina, Chris H. Wiggins, Michael L. Dustin. "Integrative analysis of T cell motility from multi-channel microscopy data using TIAM." JIM - Journal of Immunological Methods (2015) 84-93

COVID-19 CT image segmentation method based on swin transformer

Weiwei Sun, Jungang Chen, Li Yan, Jinzhao Lin, Yu Pang, Guo Zhang
2022 Frontiers in Physiology  

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In this study, we propose a new method to improve U-Net for lesion segmentation in the chest CT images of COVID-19 patients. 750 annotated chest CT images of 150 patients diagnosed with COVID-19 were selected  ...  First, to address the problem of a loss of lesion detail during down sampling, we replaced part of the convolution operation with atrous convolution in the encoder structure of the segmentation network  ...  The main reason is the benefit from introducing W-MSA and the exchange of information.  ... 
doi:10.3389/fphys.2022.981463 pmid:36072854 pmcid:PMC9441795 fatcat:6xezoycivndmji774fw3mvuvzy
DOAJ
Citation

Weiwei Sun, Jungang Chen, Li Yan, Jinzhao Lin, Yu Pang, Guo Zhang. "COVID-19 CT image segmentation method based on swin transformer." Frontiers in Physiology (2022) 981463

An Intestinal Centerline Extraction Algorithm Based on Federated Framework

Xiaodong Wang, Zhe'nan He, Ying Wang, Linlin Dang, Weifang Han, Cheng Zhang, Yinbin Miao
2021 Wireless Communications and Mobile Computing  

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Fully excavate the multiscale features of samples, to construct a fusion enhancement model and intestinal segmentation module for accurate positioning.  ...  At the local end, the centerline extraction algorithm is optimized, with the edge as the main and the source as the auxiliary to realize centerline extraction.  ...  The deep learning model [23, 24] converts the image segmentation problem into a probability problem, learns data with labeled information, and achieves target segmentation.  ... 
doi:10.1155/2021/2979214 fatcat:lvfvsv34afh2znqgfnyhxj5gjq
DOAJ
Citation

Xiaodong Wang, Zhe'nan He, Ying Wang, Linlin Dang, Weifang Han, Cheng Zhang, Yinbin Miao. "An Intestinal Centerline Extraction Algorithm Based on Federated Framework." Wireless Communications and Mobile Computing (2021) 1-12

Enhancing 6-DoF Object Pose Estimation through Multiple Modality Fusion: A Hybrid CNN Architecture with Cross-Layer and Cross-Modal Integration

Zihang Wang, Xueying Sun, Hao Wei, Qing Ma, Qiang Zhang
2023 Machines  

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The CM and CL integration strategy significantly enhanced the segmentation accuracy by effectively capturing spatial and contextual information.  ...  Furthermore, we introduced the Convolutional Block Attention Module (CBAM), which dynamically recalibrated the feature maps, enabling the network to focus on informative regions and channels, thereby enhancing  ...  For a given estimated pose [R|T] and the ground truth pose [R|T], ADD-S computes the average distance of each 3D model point transformed by [R|T] to its nearest neighbor on the target model transformed  ... 
doi:10.3390/machines11090891 fatcat:uf5dksembvhnrcanabpviwat34
DOAJ
Citation

Zihang Wang, Xueying Sun, Hao Wei, Qing Ma, Qiang Zhang. "Enhancing 6-DoF Object Pose Estimation through Multiple Modality Fusion: A Hybrid CNN Architecture with Cross-Layer and Cross-Modal Integration." Machines 11.9 (2023) 891

A Survey of Multimedia Technologies and Robust Algorithms [article]

Zijian Kuang, Xinran Tie
2021 arXiv   pre-print

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2021 pre-print
arXiv:2103.13477v1 fatcat:a3sijusa6jczxmy477hpcs5q5u
This survey provides an overview of multimedia technologies and robust algorithms in multimedia data processing, medical multimedia processing, human facial expression tracking and pose recognition, and  ...  technologies are now more practical and deployable in real life, and the algorithms are widely used in various researching areas such as deep learning, signal processing, haptics, computer vision, robotics, and medical  ...  Medical multimedia information processing aims to perform medical image segmentation and analysis in a fully automatic way to provide more accurate medical diagnostics information.  ... 
arXiv:2103.13477v2 fatcat:ondhsqzf3fcw5cyp24zlmyli34
Multiple Versions
Citation

Zijian Kuang, Xinran Tie. "A Survey of Multimedia Technologies and Robust Algorithms." arXiv (2021)

A survey on attention mechanisms for medical applications: are we moving towards better algorithms? [article]

Tiago Gonçalves, Isabel Rio-Torto, Luís F. Teixeira, Jaime S. Cardoso
2022 arXiv   pre-print

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image classification with three different use cases.  ...  With this motto, this paper extensively reviews the use of attention mechanisms in machine learning (including Transformers) for several medical applications.  ...  Acknowledgements This work, developed within the scope of the project "TAMI -Transparent Artificial Medical Intelligence" (NORTE-01-0247-FEDER-045905), is co-financed by ERDF -European Regional Fund through  ... 
arXiv:2204.12406v1 fatcat:lwz3hvd44bfqnhf7n57ejehidu
Open Access
Citation

Tiago Gonçalves, Isabel Rio-Torto, Luís F. Teixeira, Jaime S. Cardoso. "A survey on attention mechanisms for medical applications: are we moving towards better algorithms?." arXiv (2022)

CKD-TransBTS: Clinical Knowledge-Driven Hybrid Transformer with Modality-Correlated Cross-Attention for Brain Tumor Segmentation [article]

Jianwei Lin, Jiatai Lin, Cheng Lu, Hao Chen, Huan Lin, Bingchao Zhao, Zhenwei Shi, Bingjiang Qiu, Xipeng Pan, Zeyan Xu, Biao Huang, Changhong Liang (+3 others)
2022 arXiv   pre-print

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The proposed model inherits the strengths from both Transformer and CNN with the local feature representation ability for precise lesion boundaries and long-range feature extraction for 3D volumetric images  ...  Brain tumor segmentation (BTS) in magnetic resonance image (MRI) is crucial for brain tumor diagnosis, cancer management and research purposes.  ...  With the great success of the multi-head self-attention mechanism, transformer-based models are equally important in medical image segmentation [6] , especially for 3D volumetric images.  ... 
arXiv:2207.07370v1 fatcat:rvjpne27qrfhjgg2ccbseisefq
Open Access
Citation

Jianwei Lin, Jiatai Lin, Cheng Lu, Hao Chen, Huan Lin, Bingchao Zhao, Zhenwei Shi, Bingjiang Qiu, Xipeng Pan, Zeyan Xu, Biao Huang, Changhong Liang, Guoqiang Han, Zaiyi Liu, Chu Han. "CKD-TransBTS: Clinical Knowledge-Driven Hybrid Transformer with Modality-Correlated Cross-Attention for Brain Tumor Segmentation." arXiv (2022)

Special issue on video and imaging systems for critical engineering applications [SI 1096]

Gwanggil Jeon, Awais Ahmad, Abdellah Chehri, Salvatore Cuomo
2020 Multimedia tools and applications  

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, harsh environment, requires the growth of multifunctional, scalable imaging suit of sensors, solutions driven by novelty, operating on diverse detection and imaging principles.  ...  Moreover, artificial neural network when combined with pattern recognition techniques, such  ...  Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.  ... 
doi:10.1007/s11042-020-08672-5 fatcat:dmusbepcancb5i6jqo7hhf6a2m
Citation

Gwanggil Jeon, Awais Ahmad, Abdellah Chehri, Salvatore Cuomo. "Special issue on video and imaging systems for critical engineering applications [SI 1096]." Multimedia tools and applications 79.13-14 (2020)

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