NiftyNet: a deep-learning platform for medical imaging

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Items 101–200 of 550

1. Deep Learning Convolutional Neural Networks for the Automatic Quantification of Muscle Fat Infiltration Following Whiplash Injury
   Kenneth Arnold Weber II, Andrew C. Smith, Marie Wasielewski, Kamran Eghtesad, Pranav A. Upadhyayula, Max Wintermark, Trevor J. Hastie, Todd B. Parrish, Sean Mackey, James Matthew Elliott · 2019 · Scientific Reports
2. Split-Attention U-Net: A Fully Convolutional Network for Robust Multi-Label Segmentation from Brain MRI
   Minho Lee, Jee Young Kim, Regina E. Y. Kim, Hyun Gi Kim, Se Won Oh, Min Kyoung Lee, Sheng‐Min Wang, Nak-Young Kim, Dong Woo Kang, ZunHyan Rieu et al. · 2020 · Brain Sciences
3. Innovative strategies and challenges mosquito-borne disease control amidst climate change
   Yuan Zhang, Minhao Wang, Mingliu Huang, Jinyi Zhao · 2024 · Frontiers in Microbiology
4. Multi-organ segmentation of the head and neck area: an efficient hierarchical neural networks approach
   Elias Tappeiner, Samuel Pröll, Markus Hönig, Patrik Raudaschl, Paolo Zaffino, Maria Francesca Spadea, Gregory Charles Sharp, Rainer Schubert, Karl David Fritscher · 2019 · International Journal of Computer Assisted Radiology and Surgery
5. An Augmentation Strategy for Medical Image Processing Based on Statistical Shape Model and 3D Thin Plate Spline for Deep Learning
   Zhixian Tang, Kun Chen, Mingyuan Pan, Manning Wang, Zhijian Song · 2019 · IEEE Access
6. Robustness study of noisy annotation in deep learning based medical image segmentation
   Shaode Yu, Mingli Chen, Erlei Zhang, Junjie Wu, Hang Yu, Zi Yang, Lin Ma, Xuejun Gu, Weiguo Lu · 2020 · Physics in Medicine and Biology
7. COLI‐Net : Deep learning‐assisted fully automated COVID ‐19 lung and infection pneumonia lesion detection and segmentation from chest computed tomography images
   Isaac Shiri, Hossein Arabi, Yazdan Salimi, Amirhossein Sanaat, Azadeh Akhavanallaf, Ghasem Hajianfar, Dariush Askari, Shakiba Moradi, Zahra Mansouri, Masoumeh Pakbin et al. · 2021 · International Journal of Imaging Systems and Technology
8. Generalized Wasserstein Dice Score, Distributionally Robust Deep Learning, and Ranger for Brain Tumor Segmentation: BraTS 2020 Challenge
   Lucas Fidon, Sebastien Ourselin A, Tom K. Vercauteren · 2021 · Lecture notes in computer science
9. On brain atlas choice and automatic segmentation methods: a comparison of MAPER & FreeSurfer using three atlas databases
   Siti N. Yaakub, Rolf A. Heckemann, Simon Sean Keller, Colm J. McGinnity, Bernd Weber, Alexander Hammers · 2020 · Scientific Reports
10. Test-Time Unsupervised Domain Adaptation
    Thomas Varsavsky, Mauricio Orbes‐Arteaga, Carole H. Sudre, Mark S. Graham, Parashkev Nachev, M. Jorge Cardoso · 2020 · Lecture notes in computer science
11. Non-invasive single-cell morphometry in living bacterial biofilms
    Mingxing Zhang, Ji Zhang, Yibo Wang, Jie Wang, Alecia M. Achimovich, Scott T. Acton, Andreas Gahlmann · 2020 · Nature Communications
12. Breast cancer detection from histopathology images using modified residual neural networks
    Varun Gupta, Megha Vasudev, Amit Doegar, Nitigya Sambyal · 2021 · Journal of Applied Biomedicine
13. A State-of-the-Art Survey on Deep Learning Methods for Detection of Architectural Distortion From Digital Mammography
    Olaide Nathaniel Oyelade, Absalom El-Shamir Ezugwu · 2020 · IEEE Access
14. Adversarial Deformation Regularization for Training Image Registration Neural Networks
    Yipeng Hu, Eli Gibson, Nooshin Ghavami, Ester Bonmati, Caroline M. Moore, Mark Emberton, Tom K. Vercauteren, J. Alison Noble, Dean C. Barratt · 2018 · Lecture notes in computer science
15. Radiomics
    Martijn P. A. Starmans, Sebastian R. van der Voort, Jose M. Castillo Tovar, Jifke F. Veenland, Stefan Klein, Wiro J. Niessen · 2019 · Elsevier eBooks
16. Label-driven magnetic resonance imaging (MRI)-transrectal ultrasound (TRUS) registration using weakly supervised learning for MRI-guided prostate radiotherapy
    Qiulan Zeng, Yabo Fu, Zhen Tian, Yang Lei, Yupei Zhang, Tonghe Wang, Hui Z. Mao, Tian Liu, Walter John Curran, Ashesh B. Jani et al. · 2020 · Physics in Medicine and Biology
17. The federated tumor segmentation (FeTS) tool: an open-source solution to further solid tumor research
    Pati, Sarthak, Baid, Ujjwal, Edwards, Brandon, Sheller, Micah J, Foley, Patrick, Anthony Reina, G, Thakur, Siddhesh, Sako, Chiharu, Bilello, Michel, Davatzikos, Christos et al. · 2022 · Physics in Medicine & Biology
18. ω -net: Dual supervised medical image segmentation with multi-dimensional self-attention and diversely-connected multi-scale convolution
    Zhenghua Xu, Shijie Liu, Yuan Di, Lei Wang, Junyang Chen, Thomas Lukasiewicz, Zhigang Fu, Rui Zhang · 2022 · Neurocomputing
19. Automatic Segmentation of Vestibular Schwannoma from T2-Weighted MRI by Deep Spatial Attention with Hardness-Weighted Loss
    Guotai Wang, Jonathan Shapey, Wenqi Li, Reuben Dorent, Alexis Dimitriadis, Sotirios Bisdas, Ian Paddick, Robert Bradford, Shaoting Zhang, Sebastien Ourselin A et al. · 2019 · Lecture notes in computer science
20. Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientations
    Ayman Al‐Kababji, Fayçal Bensaali, Sarada Prasad Dakua, Yassine Himeur · 2022 · Engineering Applications of Artificial Intelligence
21. medigan: a Python library of pretrained generative models for medical image synthesis
    Richard O. Osuala, Grzegorz Skorupko, Noussair Lazrak, Lidia Garrucho, Eloy García, Smriti Joshi, Socayna Jouide, Michael Rutherford, Fred Prior, Kaisar Kushibar et al. · 2023 · Journal of medical imaging
22. An Automated Localization, Segmentation and Reconstruction Framework for Fetal Brain MRI
    Michael Ebner, Guotai Wang, Wenqi Li, Michaël Aertsen, Premal Amrishkumar Patel, Rosalind Aughwane, Andrew Melbourne, Tom Doel, Anna Louise David, Jan A. Deprest et al. · 2018 · Lecture notes in computer science
23. PRDL: Relative Localization Method of RFID Tags via Phase and RSSI Based on Deep Learning
    Leixian Shen, Qingyun Zhang, Jiayi Pang, He Xu, Peng Li · 2019 · IEEE Access
24. Deep Learning‐Based Techniques in Glioma Brain Tumor Segmentation Using Multi‐Parametric MRI : A Review on Clinical Applications and Future Outlooks
    Delaram J. Ghadimi, Amir Mohammad Vahdani, Hanie Karimi, Pouya Ebrahimi, Mobina Fathi, Farzan Moodi, Adrina Habibzadeh, Fereshteh Khodadadi Shoushtari, Gelareh Valizadeh, Hanieh Mobarak Salari et al. · 2024 · Journal of Magnetic Resonance Imaging
25. Automatic segmentation of mitochondria and endolysosomes in volumetric electron microscopy data
    Manca Žerovnik Mekuč, Ciril Bohak, Samo Hudoklin, Byeong Hak Kim, Rok Romih, Min Young Kim, Matija Marolt · 2020 · Computers in Biology and Medicine
26. Computer-aided diagnosis systems for osteoporosis detection: a comprehensive survey
    Insha Majeed Wani, Sakshi Arora · 2020 · Medical & Biological Engineering & Computing
27. DeepReg: a deep learning toolkit for medical image registration
    Yunguan Fu, Nina Montaña Brown, Shaheer U. Saeed, Adrià Casamitjana, Zachary Michael Cieman Baum, R. Delaunay, Qian-Ye Yang, A. Grimwood, Z. Min, Stefano B. Blumberg et al. · 2020 · Journal of Open Source Software
28. Feasibility of Deep Learning-Guided Attenuation and Scatter Correction of Whole-Body 68Ga-PSMA PET Studies in the Image Domain
    Samaneh Mostafapour, Faeze Gholamiankhah, Habibollah Dadgar, Hossein Arabi, Habib Zaidi · 2021 · Clinical Nuclear Medicine
29. Incorporating prior knowledge via volumetric deep residual network to optimize the reconstruction of sparsely sampled MRI
    Yan Wu, Yajun Ma, Dante P. I. Capaldi, Jing Liu, Wei Zhao, Jiang Du, Lei Xing · 2019 · Magnetic Resonance Imaging
30. Deep Learning for Predictive Analytics in Healthcare
    Anandhavalli Muniasamy, Sehrish Tabassam, Mohammad Ashfaq Hussain, Habeeba Sultana, Vasanthi Muniasamy, Roheet Bhatnagar · 2019 · Advances in intelligent systems and computing
31. Truncation compensation and metallic dental implant artefact reduction in PET/MRI attenuation correction using deep learning-based object completion
    Hossein Arabi, Habib Zaidi · 2020 · Physics in Medicine and Biology
32. Uncertainty in Multitask Learning: Joint Representations for Probabilistic MR-only Radiotherapy Planning
    Bragman, FJS, Ryutaro Tanno, Zach Eaton-Rosen, Wenqi Li, Hawkes, DJ, Sebastien Ourselin A, Daniel C. Alexander, McClelland, JR, M. Jorge Cardoso · 2018 · UCL Discovery (University College London)
33. Colonoscopic image synthesis with generative adversarial network for enhanced detection of sessile serrated lesions using convolutional neural network
    Dan Yoon, Hyoun‐Joong Kong, Byeong Soo Kim, Woo Sang Cho, Jung Chan Lee, Minwoo Cho, Min Hyuk Lim, Sun Young Yang, Seon Hee Lim, Jooyoung Lee et al. · 2022 · Scientific Reports
34. GaNDLF: the generally nuanced deep learning framework for scalable end-to-end clinical workflows
    Sarthak Pati, Siddhesh Pravin Thakur, İbrahim Ethem Hamamcı, Ujjwal Baid, Bhakti Baheti, Megh Bhalerao, Orhun Güley, Sofia Mouchtaris, David Lang, Spyridon Thermos et al. · 2023 · Communications Engineering
35. Generation of Realistic Synthetic Financial Time-series
    Mihai Dogariu, Liviu–Daniel Stefan, Bogdan Andrei Boteanu, Claudiu Lamba, Bomi Kim, Bogdan Emanuel Ionescu · 2022 · ACM Transactions on Multimedia Computing Communications and Applications
36. DeepNeuro: an open-source deep learning toolbox for neuroimaging
    Andrew L. Beers, James M. Brown, Ken Chang, Katharina Hoebel, Jay Patel, K. Ina Ly, Sara M. Tolaney, Priscilla Kaliopi Brastianos, Bruce Robert Rosen, Elizabeth Robins Gerstner et al. · 2020 · Neuroinformatics
37. Automatic Whole Heart Segmentation Using a Two-Stage U-Net Framework and an Adaptive Threshold Window
    Tao Liu, Yun Tian, Shifeng Zhao, Xiaoying Huang, Qingjun Wang · 2019 · IEEE Access
38. A k-Space Model of Movement Artefacts: Application to Segmentation Augmentation and Artefact Removal
    Richard Shaw, Carole H. Sudre, Thomas Varsavsky, Sebastien Ourselin A, M. Jorge Cardoso · 2020 · IEEE Transactions on Medical Imaging
39. Multi-muscle deep learning segmentation to automate the quantification of muscle fat infiltration in cervical spine conditions
    Kenneth Arnold Weber II, Rebecca Abbott, Vivie Bojilov, Andrew C. Smith, Marie Wasielewski, Trevor J. Hastie, Todd B. Parrish, Sean Mackey, James Matthew Elliott · 2021 · Scientific Reports
40. Learning image-based spatial transformations via convolutional neural networks: A review
    Nicholas James Tustison, Brian Avants, James C. Gee · 2019 · Magnetic Resonance Imaging
41. DeepTOFSino: A deep learning model for synthesizing full-dose time-of-flight bin sinograms from their corresponding low-dose sinograms
    Amirhossein Sanaat, Hossein Shooli, Sohrab Ferdowsi, Isaac Shiri, Hossein Arabi, Habib Zaidi · 2021 · NeuroImage
42. pymia: A Python package for data handling and evaluation in deep learning-based medical image analysis
    Alain Jungo, Olivier Scheidegger, Mauricio Reyes, Fabian Balsiger · 2020 · Computer Methods and Programs in Biomedicine
43. Deep learning from MRI-derived labels enables automatic brain tissue classification on human brain CT
    Meera Srikrishna, Joana B. Pereira, Rolf A. Heckemann, Giovanni Volpe, Danielle van Westen, Anna Zettergren, Silke Kern, Lars‐Olof Wahlund, Eric Westman, Ingmar Gr. Skoog et al. · 2021 · NeuroImage
44. Computer assisted recognition of breast cancer in biopsy images via fusion of nucleus-guided deep convolutional features
    Kalpana George, Praveen Sankaran, Paul Joseph K · 2020 · Computer Methods and Programs in Biomedicine
45. MR Images, Brain Lesions, and Deep Learning
    Darwin Castillo, Vasudevan Lakshminarayanan, María José Rodríguez-Álvarez · 2021 · Applied Sciences
46. ClinicaDL: An open-source deep learning software for reproducible neuroimaging processing
    Elina Thibeau–Sutre, Mauricio Díaz, Ravi Hassanaly, Alexandre Routier, Didier Dormont, Olivier Colliot, Ninon Burgos · 2022 · Computer Methods and Programs in Biomedicine
47. Enhanced Deep Learning Approach for Predicting Invasive Ductal Carcinoma from Histopathology Images
    Aiza M. Romano, Alexander Arcenio Hernandez · 2019 · International Conference on Artificial Intelligence and Big Data (ICAIBD)
48. Automatic Segmentation of Multiple Structures in Knee Arthroscopy Using Deep Learning
    Yaqub Jonmohamadi, Yu Takeda, Fengbei Liu, Fumio Sasazawa, Gabriel Maicas, Ross Crawford, Jonathan M. Roberts, Ajay Kumar Pandey, Gustavo Carneiro · 2020 · IEEE Access
49. Automatic Detection of the Aortic Annular Plane and Coronary Ostia from Multidetector Computed Tomography
    Patricio Astudillo, Peter Mortier, Johan M Bosmans, Ole De Backer, Peter P.T. de Jaegere, Francesco Iannaccone, Matthieu De Beule, Joni Dambre · 2020 · Journal of Interventional Cardiology
50. Potentials and caveats of AI in hybrid imaging
    Lalith Kumar Shiyam Sundar, Otto Muzik, Irène Buvat, Luc M. Bidaut, Thomas Beyer · 2020 · Methods
51. Doctor's Dilemma: Evaluating an Explainable Subtractive Spatial Lightweight Convolutional Neural Network for Brain Tumor Diagnosis
    Ambeshwar Kumar, R. Manikandan, Utku Köse, Deepak Kumar Gupta, Suresh Chandra Satapathy · 2021 · ACM Transactions on Multimedia Computing Communications and Applications
52. Medical Transformer: Universal Encoder for 3-D Brain MRI Analysis
    Eunji Jun, Seungwoo Jeong, Da-Woon Heo, Heung‐Il Suk · 2023 · IEEE Transactions on Neural Networks and Learning Systems
53. Kidney Segmentation in Renal Magnetic Resonance Imaging - Current Status and Prospects
    Frank Gerrit Zöllner, Marek Kociński, Laura Hansen, Alena‐Kathrin Golla, Amira Šerifović Trbalić, Arvid Lundervold, Andrzej Materka, Peter Rogelj · 2021 · IEEE Access
54. Generating diagnostic report for medical image by high-middle-level visual information incorporation on double deep learning models
    Xianhua Zeng, Li Wen, Xu Yang, Conghui Ji · 2020 · Computer Methods and Programs in Biomedicine
55. Multilayer perceptron neural network model development for mechanical ventilator parameters prediction by real time system learning
    Sita Radhakrishnan, Suresh Gangadharan Nair, Johney Isaac · 2021 · Biomedical Signal Processing and Control
56. Investigation and benchmarking of U-Nets on prostate segmentation tasks
    Shrajan Bhandary, Dejan Kuhn, Zahra Babaiee, Tobias Fechter, Matthias Benndorf, Constantinos Zamboglou, Anca‐Ligia Grosu, Radu Grosu · 2023 · Computerized Medical Imaging and Graphics
57. Deep learning in biomedical image analysis
    Minjeong Kim, Chenggang Clarence Yan, Defu Yang, Qian Wang, Junbo Ma, Guorong Wu A · 2019 · Elsevier eBooks
58. An active learning approach to train a deep learning algorithm for tumor segmentation from brain MR images
    Andrew S. Boehringer, Amirhossein Sanaat, Hossein Arabi, Habib Zaidi · 2023 · Insights into Imaging
59. ParallelNet: multiple backbone network for detection tasks on thigh bone fracture
    Mengxuan Wang, Jinkun Yao, Guoshan Zhang, Bin Guan, Xinbo Wang, Yueming Zhang · 2021 · Multimedia Systems
60. H-ProSeg: Hybrid ultrasound prostate segmentation based on explainability-guided mathematical model
    Tao Peng, Yiyun Wu, Jing Qin, Qingrong Jackie Wu, Jing Cai · 2022 · Computer Methods and Programs in Biomedicine
61. Deep Learning Aided Neuroimaging and Brain Regulation
    Mengze Xu, Yuanyuan Ouyang, Zhen Yuan · 2023 · Sensors
62. Deep learning‐based reconstruction of in vivo pelvis conductivity with a 3D patch‐based convolutional neural network trained on simulated MR data
    Soraya Gavazzi, Cornelis A. T. van den Berg, M.H.F. Savenije, Henny Petra Kok, Peter de Boer, Lukas J.A. Stalpers, J J W Lagendijk, Johannes Crezee, Astrid L.H.M.W. van Lier · 2020 · Magnetic Resonance in Medicine
63. Automatic segmentation of human knee anatomy by a convolutional neural network applying a 3D MRI protocol
    Carl Petter Skaar Kulseng, Varatharajan Nainamalai, Endre Grøvik, Jonn Terje Geitung, Asbjørn Årøen, Kjell‐Inge Gjesdal · 2023 · BMC Musculoskeletal Disorders
64. An overview of deep learning techniques for COVID-19 detection: methods, challenges, and future works
    Ercan Gürsoy, Yasin Kaya · 2023 · Multimedia Systems
65. A Practical Review on Medical Image Registration: From Rigid to Deep Learning Based Approaches
    Natan Andrade, Fabio Augusto Faria, Fábio A. M. Cappabianco · 2018 · SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)
66. Task Decomposition and Synchronization for Semantic Biomedical Image Segmentation
    Xuhua Ren, Sahar Ahmad, Lichi Zhang, Lei Xiang, Dong Nie, Fan Yang, Qian Wang, Dinggang G. Shen · 2020 · IEEE Transactions on Image Processing
67. Enhanced Rotation-Equivariant U-Net for Nuclear Segmentation
    Benjamin Chidester, That-Vinh Ton, Minh–Triet Tran, Jian Ma, Minh N. Do · 2019 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
68. Classification and Visualisation of Normal and Abnormal Radiographs; A Comparison between Eleven Convolutional Neural Network Architectures
    Ananda Ananda, Kwun Ho Ngan, Cefa Karabağ, Aram Ter-Sarkisov, Eduardo Alonso, Constantino Carlos Reyes‐Aldasoro · 2021 · Sensors
69. Generation of microbial colonies dataset with deep learning style transfer
    Jarosław Pawłowski, Sylwia Majchrowska, T. Golan · 2022 · Scientific Reports
70. Modern Image-Guided Surgery: A Narrative Review of Medical Image Processing and Visualization
    Zhefan Lin, Chen Lei, Liangjing Yang · 2023 · Sensors
71. Advances in Deep Learning Techniques for Medical Image Analysis
    Usma Niyaz, Abhishek Singh Sambyal, Devanand · 2018 · International Conference on Parallel, Distributed and Grid Computing (PDGC)
72. Research on Risk Prediction of Dyslipidemia in Steel Workers Based on Recurrent Neural Network and LSTM Neural Network
    Shiyue Cui, Chao Li, Zhe Chen, Jiaojiao Wang, Juxiang Yuan · 2020 · IEEE Access
73. Unlocking the potential: the influence of sustainable finance solutions on the long-term sustainability of small and medium-sized enterprises
    Ahmed Idi Kato, Germinah Evelyn Chiloane-Tsoka, Paddy Mugambe · 2024 · Cogent Business & Management
74. Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer
    Paul Blanc‐Durand, Luca Campedel, Sebastien Mulé, Simon Jégou, Alain Luciani, Frederic Pigneur, Emmanuel Itti · 2020 · European Radiology
75. Robust Deep Learning–based Segmentation of Glioblastoma on Routine Clinical MRI Scans Using Sparsified Training
    Roelant S. Eijgelaar, Martin Visser, Domenique M. J. Müller, Frederik Barkhof, Hugo Vrenken, Marcel van Herk, Lorenzo Bello, Marco Conti Nibali, Marco Rossi, Tommaso Sciortino et al. · 2020 · Radiology Artificial Intelligence
76. DeepDose: a robust deep learning-based dose engine for abdominal tumours in a 1.5 T MRI radiotherapy system
    Georgios Tsekas, G.H. Bol, Bas W. Raaymakers, C Kontaxis · 2021 · Physics in Medicine and Biology
77. Fatty infiltration in cervical flexors and extensors in patients with degenerative cervical myelopathy using a multi-muscle segmentation model
    Monica Paliwal, Kenneth Arnold Weber II, Andrew C. Smith, James Matthew Elliott, Fauziyya Muhammad, Nader S. Dahdaleh, Jerzy Bodurka, Yasin Y. Dhaher, Todd B. Parrish, Sean Mackey et al. · 2021 · PLoS ONE
78. Artificial intelligence in tumor subregion analysis based on medical imaging: A review
    Mingquan Lin, Jacob Frank Wynne, Boran Zhou, Tonghe Wang, Yang Lei, Walter John Curran, Tian Liu, Xiaofeng Yang · 2021 · Journal of Applied Clinical Medical Physics
79. Deep learning methods for automatic segmentation of lower leg muscles and bones from MRI scans of children with and without cerebral palsy
    Jiayi Zhu, Bart Bolsterlee, Brian V. Y. Chow, Chengxue Cai, Rob Herbert, Yang Song, Erik H. W. Meijering · 2021 · NMR in Biomedicine
80. Development and External Validation of a Deep Learning Algorithm to Identify and Localize Subarachnoid Hemorrhage on CT Scans
    Antonios-Konstantinos Thanellas, Heikki Peura, Mikko Lavinto, Tomi Ruokola, Moira Vieli, Victor E. Staartjes, Sebastian F.-X. Winklhofer, Carlo Serra, Luca Regli, Miikka Korja · 2023 · Neurology
81. Analysis of intensity normalization for optimal segmentation performance of a fully convolutional neural network
    Nina Jacobsen, Andreas Deistung, Dagmar Timmann, Sophia L. Goericke, Jürgen Rainer Reichenbach, Daniel Güllmar · 2018 · Zeitschrift für Medizinische Physik
82. Automatic segmentation method of pelvic floor levator hiatus in ultrasound using a self-normalizing neural network
    Ester Bonmati, Yipeng Hu, Sindhwani, N, Dietz, HP, D'hooge, J, Dean C. Barratt, Jan A. Deprest, Tom K. Vercauteren · 2018 · Lirias (KU Leuven)
83. SenseCare: A Research Platform for Medical Image Informatics and Interactive 3D Visualization
    Qi Duan, Guotai Wang, Wang, Rui, Chao Fu, Li, Xinjun, Na Wang, Yechong Huang, Xiaodi Huang, Tao Song, Liang Zhao et al. · 2020 · arXiv (Cornell University)
84. Internet of Things with Deep Learning Techniques for Pandemic Detection: A Comprehensive Review of Current Trends and Open Issues
    Sunday Adeola Ajagbe, Pragasen Mudali, Matthew Olusegun Adigun · 2024 · Electronics
85. Adversarial Optimization for Joint Registration and Segmentation in Prostate CT Radiotherapy
    Mohamed S. Elmahdy, Jelmer M. Wolterink, Hessam Sokooti, Ivana Išgum, Marius Staring · 2019 · Lecture notes in computer science
86. Oxynet: A collective intelligence that detects ventilatory thresholds in cardiopulmonary exercise tests
    Andrea Zignoli, Alessandro Fornasiero, Paolo Rota, Valentina Muollo, Leonardo Alexandre Peyré‐Tartaruga, David A. Low, Federico Y. Fontana, D. Besson, Martin Pühringer, Susanne Ring‐Dimitriou et al. · 2020 · European Journal of Sport Science
87. Use of Artificial Intelligence in the Advancement of Breast Surgery and Implications for Breast Reconstruction: A Narrative Review
    Ishith Seth, Gabriella Bulloch, Konrad Joseph, David J. Hunter‐Smith, Warren M. Rozen · 2023 · Journal of Clinical Medicine
88. MR-to-US Registration Using Multiclass Segmentation of Hepatic Vasculature with a Reduced 3D U-Net
    Bart R. Thomson, Jasper N. Smit, Oleksandra Ivashchenko, Niels F.M. Kok, Koert F.D. Kuhlmann, Theo J. M. Ruers, Matteo Fusaglia · 2020 · Lecture notes in computer science
89. Application of Artificial Intelligence Algorithms Within the Medical Context for Non-Specialized Users: the CARTIER-IA Platform.
    Francisco José García‐Peñalvo, Andrea Vázquez‐Ingelmo, Alicia García‐Holgado, Jesús Sampedro-Gómez, Antonio Sánchez-Puente, Víctor Vicente-Palacios, Pedro Ignacio Dorado-Díaz, Pedro Luis Sanchez · 2021 · International Journal of Interactive Multimedia and Artificial Intelligence
90. Curriculum learning for improved femur fracture classification: Scheduling data with prior knowledge and uncertainty
    Amelia Jiménez-Sánchez, Diana Mateus, Sonja Kirchhoff, Chlodwig Kirchhoff, Peter Biberthaler, Nassir Navab, Miguel Á. González Ballester, Gemma Piella · 2021 · Medical Image Analysis
91. Uncertainty in Multitask Learning: Joint Representations for Probabilistic MR-only Radiotherapy Planning
    Felix Bragman, Ryutaro Tanno, Zach Eaton-Rosen, Wenqi Li, David J. Hawkes, Sebastien Ourselin A, Daniel C. Alexander, Jamie R. McClelland, M. Jorge Cardoso · 2018 · Lecture notes in computer science
92. Medical Transformer: Universal Brain Encoder for 3D MRI Analysis
    Eunji Jun, Seungwoo Jeong, Da-Woon Heo, Heung‐Il Suk · 2021 · arXiv (Cornell University)
93. Advancements in hybrid approaches for brain tumor segmentation in MRI: a comprehensive review of machine learning and deep learning techniques
    Ravikumar Sajjanar, Umesh D. Dixit, Vittalkumar K Vagga · 2023 · Multimedia Tools and Applications
94. Image Registration in Medical Robotics and Intelligent Systems: Fundamentals and Applications
    Jun Liu, Gurpreet Singh, Subhi Jamal Alaref, Benjamin Lee, Olachi O. Oleru, James K. Min, Simon N. Dunham, Mert Rory Sabuncu, Bobak Mosadegh · 2019 · Advanced Intelligent Systems
95. Automated machine learning to predict the co‐occurrence of isocitrate dehydrogenase mutations and O6‐methylguanine‐DNA methyltransferase promoter methylation in patients with gliomas
    Simin Zhang, Huaiqiang Sun, Xiaorui Su, Xibiao Yang, Weina Wang, Xinyue Wan, Qiaoyue Tan, Ni Chen, Qiang Yue, Qiyong Gong · 2021 · Journal of Magnetic Resonance Imaging
96. Direct inference of Patlak parametric images in whole-body PET/CT imaging using convolutional neural networks
    Neda Zaker, Kamal Hadad, Reza Faghihi, Hossein Arabi, Habib Zaidi · 2022 · European Journal of Nuclear Medicine and Molecular Imaging
97. Deep learning-guided surface characterization for autonomous hydrogen lithography
    Mohammad Rashidi, Jeremiah Croshaw, Kieran Mastel, Marcus Tamura, Hedieh Hosseinzadeh, Robert A. Wolkow · 2020 · Machine Learning Science and Technology
98. Automated Pipeline to Generate Anatomically Accurate Patient-Specific Biomechanical Models of Healthy and Pathological FSUs
    Sebastiano Caprara, Fabio Carrillo, Jess Gerrit Snedeker, Mazda Farshad, Marco Senteler · 2021 · Frontiers in Bioengineering and Biotechnology
99. μ -Net: Medical image segmentation using efficient and effective deep supervision
    Yuan Di, Zhenghua Xu, Biao Tian, Hening Wang, Yuefu Zhan, Thomas Lukasiewicz · 2023 · Computers in Biology and Medicine
100. Toward Human-centered XAI in Practice: A survey
     Xiangwei Kong, Shujie Liu, Luhao Zhu · 2024 · Machine Intelligence Research