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Magnetic resonance imaging~(MRI) have played a crucial role in brain disease diagnosis, with which a range of computer-aided artificial intelligence methods have been proposed.
D-former: A u-shaped dilated transformer for 3d medical image segmentation
Yixuan Wu et al · 1944
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Magnetic resonance imaging (mri)–a review
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Magnetic resonance imaging and computed tomography of the brain—50 years of innovation, with a focus on the future
Val M Runge, Shigeki Aoki, William G Bradley Jr, Kee-Hyun Chang, Marco Essig, Lin Ma, Jeffrey S Ross, and Anton Valavanis · 2015
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Learning spatiotemporal features with 3d convolutional networks
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Sarfaraz Hussein, Kunlin Cao, Qi Song, and Ulas Bagci · 2017
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Studying neuroanatomy using mri
Jason P Lerch, André JW Van Der Kouwe, Armin Raznahan, Tomáš Paus, Heidi Johansen-Berg, Karla L Miller, Stephen M Smith, Bruce Fischl, and Stamatios N Sotiropoulos · 2017
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Attention is all you need
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Negbio: a high-performance tool for negation and uncertainty detection in radiology reports
Yifan Peng, Xiaosong Wang, Le Lu, Mohammadhadi Bagheri, Ronald Summers, and Zhiyong Lu · 2018
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Knowledge-based collaborative deep learning for benign-malignant lung nodule classification on chest ct
Yutong Xie, Yong Xia, Jianpeng Zhang, Yang Song, Dagan Feng, Michael Fulham, and Weidong Cai · 2018
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Med3d: Transfer learning for 3d medical image analysis
Sihong Chen, Kai Ma, and Yefeng Zheng · 2019
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Attention to lesion: Lesion-aware convolutional neural network for retinal optical coherence tomography image classification
Leyuan Fang, Chong Wang, Shutao Li, Hossein Rabbani, Xiangdong Chen, and Zhimin Liu · 2019
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Clinicalbert: Modeling clinical notes and predicting hospital readmission
Kexin Huang et al · 2019
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Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison
Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Chris Chute, Henrik Marklund, Behzad Haghgoo, Robyn Ball, Katie Shpanskaya, et al · 2019
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Attention based glaucoma detection: A large-scale database and cnn model
Liu Li et al · 2019
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Embedding human knowledge into deep neural network via attention map
Masahiro Mitsuhara et al · 2019
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Expert knowledge-infused deep learning for automatic lung nodule detection
Jiaxing Tan, Yumei Huo, Zhengrong Liang, and Lihong Li · 2019
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Httu-net: Hybrid two track u-net for automatic brain tumor segmentation
Nagwa M. Aboelenein, Piao Songhao, Anis Koubaa, Alam Noor, and Ahmed Afifi · 2020
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Language models are few-shot learners
Tom Brown et al · 2020
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Joint modeling of chest radiographs and radiology reports for pulmonary edema assessment
Geeticka Chauhan, Ruizhi Liao, William Wells, Jacob Andreas, Xin Wang, Seth Berkowitz, Steven Horng, Peter Szolovits, and Polina Golland · 2020
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Deep learning-based detection and segmentation of diffusion abnormalities in acute ischemic stroke
Chin-Fu Liu, Johnny Hsu, Xin Xu, Sandhya Ramachandran, Victor Wang, Michael I Miller, Argye E Hillis, and Andreia V Faria · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Teds-net: enforcing diffeomorphisms in spatial transformers to guarantee topology preservation in segmentations
Madeleine K Wyburd et al · 2021
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A survey on incorporating domain knowledge into deep learning for medical image analysis
Xiaozheng Xie, Jianwei Niu, Xuefeng Liu, Zhengsu Chen, Shaojie Tang, and Shui Yu · 2021
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Stroke lesion detection and analysis in mri images based on deep learning
Shujun Zhang, Shuhao Xu, Liwei Tan, Hongyan Wang, and Jianli Meng · 2021
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Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 5th International Workshop, BrainLes 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Revised Selected Papers, Part II , volume 11993 of Lecture Notes in Computer Science , 2020. Springer
Alessandro Crimi and Spyridon Bakas, editors · 2020
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Dual-ray net: automatic diagnosis of thoracic diseases using frontal and lateral chest x-rays
Xin Huang et al · 2020
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Chexpert++: Approximating the chexpert labeler for speed, differentiability, and probabilistic output
Matthew BA McDermott, Tzu Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, and Peter Szolovits · 2020
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Akshay Smit et al · 2020
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Learning to recognize thoracic disease in chest x-rays with knowledge-guided deep zoom neural networks
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Alzheimer’s disease detection from brain mri data using deep learning techniques
DH Chaihtra and S Vijaya Shetty · 2021
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Transunet: Transformers make strong encoders for medical image segmentation
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Making the most of text semantics to improve biomedical vision–language processing
Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel C Castro, Anton Schwaighofer, Stephanie Hyland, Maria Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, et al · 2022
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Classification of brain tumours in mr images using deep spatiospatial models
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Unetr: Transformers for 3d medical image segmentation
Ali Hatamizadeh, Yucheng Tang, Vishwesh Nath, Dong Yang, Andriy Myronenko, Bennett Landman, Holger R Roth, and Daguang Xu · 2022
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Transbtsv2: Towards better and more efficient volumetric segmentation of medical images
Jiangyun Li, Wenxuan Wang, Chen Chen, Tianxiang Zhang, Sen Zha, Jing Wang, and Hong Yu · 2022
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Pc-swinmorph: Patch representation for unsupervised medical image registration and segmentation
Lihao Liu, Zhening Huang, Pietro Liò, Carola-Bibiane Schönlieb, and Angelica I Aviles-Rivero · 2022
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Self-supervised pre-training of swin transformers for 3d medical image analysis
Yucheng Tang, Dong Yang, Wenqi Li, Holger R Roth, Bennett Landman, Daguang Xu, Vishwesh Nath, and Ali Hatamizadeh · 2022
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Expert-level detection of pathologies from unannotated chest x-ray images via self-supervised learning
Ekin Tiu, Ellie Talius, Pujan Patel, Curtis P Langlotz, Andrew Y Ng, and Pranav Rajpurkar · 2022
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mmformer: Multimodal medical transformer for incomplete multimodal learning of brain tumor segmentation
Yao Zhang et al · 2022
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Self pre-training with masked autoencoders for medical image classification and segmentation
Lei Zhou, Huidong Liu, Joseph Bae, Junjun He, Dimitris Samaras, and Prateek Prasanna · 2022
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Medklip: Medical knowledge enhanced language-image pre-training
Chaoyi Wu, Xiaoman Zhang, Ya Zhang, Yanfeng Wang, and Weidi Xie · 2023
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Knowledge-enhanced pre-training for auto-diagnosis of chest radiology images
Xiaoman Zhang, Chaoyi Wu, Ya Zhang, Yanfeng Wang, and Weidi Xie · 2023
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