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ویرایش: 1st ed. نویسندگان: Mingxia Liu, Pingkun Yan, Chunfeng Lian, Xiaohuan Cao سری: Lecture Notes in Computer Science 12436 ISBN (شابک) : 9783030598600, 9783030598617 ناشر: Springer International Publishing;Springer سال نشر: 2020 تعداد صفحات: 701 زبان: English فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) حجم فایل: 135 مگابایت
کلمات کلیدی مربوط به کتاب یادگیری ماشین در تصویربرداری پزشکی: یازدهمین کارگاه بین المللی ، MLMI 2020 ، همراه با MICCAI 2020 ، لیما ، پرو ، 4 اکتبر 2020 ، مجموعه مقالات: است
در صورت تبدیل فایل کتاب Machine Learning in Medical Imaging: 11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب یادگیری ماشین در تصویربرداری پزشکی: یازدهمین کارگاه بین المللی ، MLMI 2020 ، همراه با MICCAI 2020 ، لیما ، پرو ، 4 اکتبر 2020 ، مجموعه مقالات نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
این کتاب مجموعه مقالات یازدهمین کارگاه بینالمللی یادگیری ماشین در تصویربرداری پزشکی، MLMI 2020 است که همزمان با MICCAI 2020، در لیما، پرو، در اکتبر 2020 برگزار شد. این کنفرانس به طور مجازی به دلیل همه گیری کووید-19.
68 مقاله ارائه شده در این جلد به دقت بررسی و از بین 101 مورد ارسالی انتخاب شدند. آنها بر روی روندها و چالشهای اصلی در حوزه فوق تمرکز میکنند و هدف آن شناسایی تکنیکهای جدید و کاربردهای آنها در تصویربرداری پزشکی است. موضوعات مورد بحث عبارتند از: یادگیری عمیق، یادگیری خصمانه مولد، یادگیری گروهی، یادگیری پراکنده، یادگیری چندکاره، یادگیری چند وجهی، یادگیری چندگانه، و یادگیری تقویتی، با کاربردهای آنها در تجزیه و تحلیل تصویر پزشکی، تشخیص و تشخیص به کمک رایانه، همجوشی چند وجهی، بازسازی تصویر، بازیابی تصویر، تجزیه و تحلیل تصویر سلولی، تصویربرداری مولکولی، آسیب شناسی دیجیتال، و غیره.
This book constitutes the proceedings of the 11th International Workshop on Machine Learning in Medical Imaging, MLMI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic.
The 68 papers presented in this volume were carefully reviewed and selected from 101 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.
Front Matter ....Pages i-xv
Temporal-Adaptive Graph Convolutional Network for Automated Identification of Major Depressive Disorder Using Resting-State fMRI (Dongren Yao, Jing Sui, Erkun Yang, Pew-Thian Yap, Dinggang Shen, Mingxia Liu)....Pages 1-10
Error Attention Interactive Segmentation of Medical Image Through Matting and Fusion (Weifeng Hu, Xiaofen Yao, Zhou Zheng, Xiaoyun Zhang, Yumin Zhong, Xiaoxia Wang et al.)....Pages 11-20
A Novel fMRI Representation Learning Framework with GAN (Qinglin Dong, Ning Qiang, Jinglei Lv, Xiang Li, Liang Dong, Tianming Liu et al.)....Pages 21-29
Semi-supervised Segmentation with Self-training Based on Quality Estimation and Refinement (Zhou Zheng, Xiaoxia Wang, Xiaoyun Zhang, Yumin Zhong, Xiaofen Yao, Ya Zhang et al.)....Pages 30-39
3D Segmentation Networks for Excessive Numbers of Classes: Distinct Bone Segmentation in Upper Bodies (Eva Schnider, Antal Horváth, Georg Rauter, Azhar Zam, Magdalena Müller-Gerbl, Philippe C. Cattin)....Pages 40-49
Super Resolution of Arterial Spin Labeling MR Imaging Using Unsupervised Multi-scale Generative Adversarial Network (Jianan Cui, Kuang Gong, Paul Han, Huafeng Liu, Quanzheng Li)....Pages 50-59
Self-recursive Contextual Network for Unsupervised 3D Medical Image Registration (Bo Hu, Shenglong Zhou, Zhiwei Xiong, Feng Wu)....Pages 60-69
Automated Tumor Proportion Scoring for Assessment of PD-L1 Expression Based on Multi-Stage Ensemble Strategy (Yuxin Kang, Hansheng Li, Xin Han, Boju Pan, Yuan Li, Yan Jin et al.)....Pages 70-79
Uncertainty Quantification in Medical Image Segmentation with Normalizing Flows (Raghavendra Selvan, Frederik Faye, Jon Middleton, Akshay Pai)....Pages 80-90
Out-of-Distribution Detection for Skin Lesion Images with Deep Isolation Forest (Xuan Li, Yuchen Lu, Christian Desrosiers, Xue Liu)....Pages 91-100
A 3D+2D CNN Approach Incorporating Boundary Loss for Stroke Lesion Segmentation (Yue Zhang, Jiong Wu, Yilong Liu, Yifan Chen, Ed X. Wu, Xiaoying Tang)....Pages 101-110
Linking Adolescent Brain MRI to Obesity via Deep Multi-cue Regression Network (Hao Guan, Erkun Yang, Li Wang, Pew-Thian Yap, Mingxia Liu, Dinggang Shen)....Pages 111-119
Robust Multiple Sclerosis Lesion Inpainting with Edge Prior (Huahong Zhang, Rohit Bakshi, Francesca Bagnato, Ipek Oguz)....Pages 120-129
Segmentation to Label: Automatic Coronary Artery Labeling from Mask Parcellation (Zhuowei Li, Qing Xia, Wenji Wang, Zhennan Yan, Ruohan Yin, Changjie Pan et al.)....Pages 130-138
GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes (Megi Isallari, Islem Rekik)....Pages 139-149
Anatomy-Aware Cardiac Motion Estimation (Pingjun Chen, Xiao Chen, Eric Z. Chen, Hanchao Yu, Terrence Chen, Shanhui Sun)....Pages 150-159
Division and Fusion: Rethink Convolutional Kernels for 3D Medical Image Segmentation (Xi Fang, Thomas Sanford, Baris Turkbey, Sheng Xu, Bradford J. Wood, Pingkun Yan)....Pages 160-169
LDGAN: Longitudinal-Diagnostic Generative Adversarial Network for Disease Progression Prediction with Missing Structural MRI (Zhenyuan Ning, Yu Zhang, Yongsheng Pan, Tao Zhong, Mingxia Liu, Dinggang Shen)....Pages 170-179
Unsupervised MRI Homogenization: Application to Pediatric Anterior Visual Pathway Segmentation (Carlos Tor-Diez, Antonio Reyes Porras, Roger J. Packer, Robert A. Avery, Marius George Linguraru)....Pages 180-188
Boundary-Aware Network for Kidney Tumor Segmentation (Shishuai Hu, Jianpeng Zhang, Yong Xia)....Pages 189-198
O-Net: An Overall Convolutional Network for Segmentation Tasks (Omid Haji Maghsoudi, Aimilia Gastounioti, Lauren Pantalone, Christos Davatzikos, Spyridon Bakas, Despina Kontos)....Pages 199-209
Label-Driven Brain Deformable Registration Using Structural Similarity and Nonoverlap Constraints (Shunbo Hu, Lintao Zhang, Yan Xu, Dinggang Shen)....Pages 210-219
EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis (Kevin Pan, Guillem Hurault, Kai Arulkumaran, Hywel C. Williams, Reiko J. Tanaka)....Pages 220-230
Deep Distance Map Regression Network with Shape-Aware Loss for Imbalanced Medical Image Segmentation (Huiyu Li, Xiabi Liu, Said Boumaraf, Xiaopeng Gong, Donghai Liao, Xiaohong Ma)....Pages 231-240
Joint Appearance-Feature Domain Adaptation: Application to QSM Segmentation Transfer (Bin Xiao, Naying He, Qian Wang, Zhong Xue, Lei Chen, Fuhua Yan et al.)....Pages 241-249
Exploring Functional Difference Between Gyri and Sulci via Region-Specific 1D Convolutional Neural Networks (Mingxin Jiang, Shimin Yang, Jiadong Yan, Shu Zhang, Huan Liu, Lin Zhao et al.)....Pages 250-259
Detection of Ischemic Infarct Core in Non-contrast Computed Tomography (Maximilian Hornung, Oliver Taubmann, Hendrik Ditt, Björn Menze, Pawel Herman, Erik Fransén)....Pages 260-269
Bayesian Neural Networks for Uncertainty Estimation of Imaging Biomarkers (Jyotirmay Senapati, Abhijit Guha Roy, Sebastian Pölsterl, Daniel Gutmann, Sergios Gatidis, Christopher Schlett et al.)....Pages 270-280
Extended Capture Range of Rigid 2D/3D Registration by Estimating Riemannian Pose Gradients (Wenhao Gu, Cong Gao, Robert Grupp, Javad Fotouhi, Mathias Unberath)....Pages 281-291
Structural Connectivity Enriched Functional Brain Network Using Simplex Regression with GraphNet (Mansu Kim, Jingxaun Bao, Kefei Liu, Bo-yong Park, Hyunjin Park, Li Shen)....Pages 292-302
Constructing High-Order Dynamic Functional Connectivity Networks from Resting-State fMRI for Brain Dementia Identification (Chunxiang Feng, Biao Jie, Xintao Ding, Daoqiang Zhang, Mingxia Liu)....Pages 303-311
Multi-tasking Siamese Networks for Breast Mass Detection Using Dual-View Mammogram Matching (Yutong Yan, Pierre-Henri Conze, Mathieu Lamard, Gwenolé Quellec, Béatrice Cochener, Gouenou Coatrieux)....Pages 312-321
3D Volume Reconstruction from Single Lateral X-Ray Image via Cross-Modal Discrete Embedding Transition (Yikun Jiang, Peixin Li, Yungeng Zhang, Yuru Pei, Yuke Guo, Tianmin Xu et al.)....Pages 322-331
Cleft Volume Estimation and Maxilla Completion Using Cascaded Deep Neural Networks (Yungeng Zhang, Yuru Pei, Yuke Guo, Si Chen, Tianmin Xu, Hongbin Zha)....Pages 332-341
A Deep Network for Joint Registration and Reconstruction of Images with Pathologies (Xu Han, Zhengyang Shen, Zhenlin Xu, Spyridon Bakas, Hamed Akbari, Michel Bilello et al.)....Pages 342-352
Learning Conditional Deformable Shape Templates for Brain Anatomy (Evan M. Yu, Adrian V. Dalca, Mert R. Sabuncu)....Pages 353-362
Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity (Nicha C. Dvornek, Xiaoxiao Li, Juntang Zhuang, Pamela Ventola, James S. Duncan)....Pages 363-372
Unsupervised Learning for Spherical Surface Registration (Fenqiang Zhao, Zhengwang Wu, Li Wang, Weili Lin, Shunren Xia, Dinggang Shen et al.)....Pages 373-383
Anatomy-Guided Convolutional Neural Network for Motion Correction in Fetal Brain MRI (Yuchen Pei, Lisheng Wang, Fenqiang Zhao, Tao Zhong, Lufan Liao, Dinggang Shen et al.)....Pages 384-393
Gyral Growth Patterns of Macaque Brains Revealed by Scattered Orthogonal Nonnegative Matrix Factorization (Songyao Zhang, Lei Du, Jinglei Lv, Zhibin He, Xi Jiang, Lei Guo et al.)....Pages 394-403
Inhomogeneity Correction in Magnetic Resonance Images Using Deep Image Priors (Shuo Han, Jerry L. Prince, Aaron Carass)....Pages 404-413
Hierarchical and Robust Pathology Image Reading for High-Throughput Cervical Abnormality Screening (Ming Zhou, Lichi Zhang, Xiaping Du, Xi Ouyang, Xin Zhang, Qijia Shen et al.)....Pages 414-422
Importance Driven Continual Learning for Segmentation Across Domains (Sinan Özgün, Anne-Marie Rickmann, Abhijit Guha Roy, Christian Wachinger)....Pages 423-433
RDCNet: Instance Segmentation with a Minimalist Recurrent Residual Network (Raphael Ortiz, Gustavo de Medeiros, Antoine H. F. M. Peters, Prisca Liberali, Markus Rempfler)....Pages 434-443
Automatic Segmentation of Achilles Tendon Tissues Using Deep Convolutional Neural Network (Tariq Alzyadat, Stephan Praet, Girija Chetty, Roland Goecke, David Hughes, Dinesh Kumar et al.)....Pages 444-454
An End to End System for Measuring Axon Growth (Zewen Liu, Timothy Cootes, Christoph Ballestrem)....Pages 455-464
Interwound Structural and Functional Difference Between Preterm and Term Infant Brains Revealed by Multi-view CCA (Zhibin He, Shu Zhang, Songyao Zhang, Yin Zhang, Xintao Hu, Xi Jiang et al.)....Pages 465-473
Graph Convolutional Network Based Point Cloud for Head and Neck Vessel Labeling (Linlin Yao, Pengbo Jiang, Zhong Xue, Yiqiang Zhan, Dijia Wu, Lichi Zhang et al.)....Pages 474-483
Unsupervised Learning-Based Nonrigid Registration of High Resolution Histology Images (Marek Wodzinski, Henning Müller)....Pages 484-493
Additive Angular Margin for Few Shot Learning to Classify Clinical Endoscopy Images (Sharib Ali, Binod Bhattarai, Tae-Kyun Kim, Jens Rittscher)....Pages 494-503
Extracting and Leveraging Nodule Features with Lung Inpainting for Local Feature Augmentation (Sebastian Gündel, Arnaud A. A. Setio, Sasa Grbic, Andreas Maier, Dorin Comaniciu)....Pages 504-512
Gambling Adversarial Nets for Hard Sample Mining and Structured Prediction: Application in Ultrasound Thyroid Nodule Segmentation (Masoumeh Bakhtiariziabari, Mohsen Ghafoorian)....Pages 513-522
Mammographic Image Conversion Between Source and Target Acquisition Systems Using cGAN (Zahra Ghanian, Andreu Badal, Kenny Cha, Mohammad Mehdi Farhangi, Nicholas Petrick, Berkman Sahiner)....Pages 523-531
An End-to-End Learnable Flow Regularized Model for Brain Tumor Segmentation (Yan Shen, Zhanghexuan Ji, Mingchen Gao)....Pages 532-541
Neural Architecture Search for Microscopy Cell Segmentation (Yanming Zhu, Erik Meijering)....Pages 542-551
Classification of Ulcerative Colitis Severity in Colonoscopy Videos Using Vascular Pattern Detection (Md Farhad Mokter, JungHwan Oh, Wallapak Tavanapong, Johnny Wong, Piet C. de Groen)....Pages 552-562
Predicting Catheter Ablation Outcomes with Pre-ablation Heart Rhythm Data: Less Is More (Lisa Y. W. Tang, Kendall Ho, Roger C. Tam, Nathaniel M. Hawkins, Michael Lim, Jason G. Andrade)....Pages 563-571
AdaBoosted Deep Ensembles: Getting Maximum Performance Out of Small Training Datasets (Syed M. S. Reza, John A. Butman, Deric M. Park, Dzung L. Pham, Snehashis Roy)....Pages 572-582
Cross-Task Representation Learning for Anatomical Landmark Detection (Zeyu Fu, Jianbo Jiao, Michael Suttie, J. Alison Noble)....Pages 583-592
Cycle Ynet: Semi-supervised Tracking of 3D Anatomical Landmarks (Jianzhe Lin, Yue Zhang, Abdoul-aziz Amadou, Ingmar Voigt, Tommaso Mansi, Rui Liao)....Pages 593-602
Learning Hierarchical Semantic Correspondence and Gland Instance Segmentation (Pei Wang, Albert C. S. Chung)....Pages 603-613
Open-Set Recognition for Skin Lesions Using Dermoscopic Images (Pranav Budhwant, Sumeet Shinde, Madhura Ingalhalikar)....Pages 614-623
End-to-End Coordinate Regression Model with Attention-Guided Mechanism for Landmark Localization in 3D Medical Images (Jupeng Li, Yinghui Wang, Junbo Mao, Gang Li, Ruohan Ma)....Pages 624-633
Enhanced MRI Reconstruction Network Using Neural Architecture Search (Qiaoying Huang, Dong yang, Yikun Xian, Pengxiang Wu, Jingru Yi, Hui Qu et al.)....Pages 634-643
Learning Invariant Feature Representation to Improve Generalization Across Chest X-Ray Datasets (Sandesh Ghimire, Satyananda Kashyap, Joy T. Wu, Alexandros Karargyris, Mehdi Moradi)....Pages 644-653
Noise-Aware Standard-Dose PET Reconstruction Using General and Adaptive Robust Loss (Lei Xiang, Long Wang, Enhao Gong, Greg Zaharchuk, Tao Zhang)....Pages 654-662
Semi-supervised Transfer Learning for Infant Cerebellum Tissue Segmentation (Yue Sun, Kun Gao, Sijie Niu, Weili Lin, Gang Li, Li Wang et al.)....Pages 663-673
Informative Feature-Guided Siamese Network for Early Diagnosis of Autism (Kun Gao, Yue Sun, Sijie Niu, Li Wang)....Pages 674-682
Back Matter ....Pages 683-686