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Publication search results
found 1,678 matches
- 2024
- Lijuan Cui, Dengao Li, Xiaofeng Yang, Chao Liu, Xiaoting Yan:
A Unified Approach Addressing Class Imbalance in Magnetic Resonance Image for Deep Learning Models. IEEE Access 12: 27368-27384 (2024) - Mamta Juneja, Ashwani Rathee, Rishabh Verma, Raag Bhutani, Shashank Baghel, Sumindar Kaur Saini, Prashant Jindal:
Denoising of magnetic resonance images of brain tumor using BT-Autonet. Biomed. Signal Process. Control. 87(Part B): 105477 (2024) - Deependra Rastogi, Prashant Johri, Varun Tiwari, Ahmed A. Elngar:
Multi-class classification of brain tumour magnetic resonance images using multi-branch network with inception block and five-fold cross validation deep learning framework. Biomed. Signal Process. Control. 88(Part A): 105602 (2024) - Imene Mecheter, Maysam Abbod, Habib Zaidi, Abbes Amira:
Transfer learning from T1-weighted to T2-weighted Magnetic resonance sequences for brain image segmentation. CAAI Trans. Intell. Technol. 9(1): 26-39 (2024) - Chunhong Cao, Wenwei Huang, Fang Hu, Xieping Gao:
Hierarchical neural architecture search with adaptive global-local feature learning for Magnetic Resonance Image reconstruction. Comput. Biol. Medicine 168: 107774 (2024) - Biao Qu, Jialue Zhang, Taishan Kang, Jianzhong Lin, Meijin Lin, Huajun She, Qingxia Wu, Meiyun Wang, Gaofeng Zheng:
Radial magnetic resonance image reconstruction with a deep unrolled projected fast iterative soft-thresholding network. Comput. Biol. Medicine 168: 107707 (2024) - Bakhtiar Amaludin, Seifedine Kadry, Fung Fung Ting, David Taniar:
Toward more accurate diagnosis of multiple sclerosis: Automated lesion segmentation in brain magnetic resonance image using modified U-Net model. Int. J. Imaging Syst. Technol. 34(1) (2024) - Sevket Ay, Ekin Ekinci, Zeynep Garip:
A brain tumour classification on the magnetic resonance images using convolutional neural network based privacy-preserving federated learning. Int. J. Imaging Syst. Technol. 34(1) (2024) - Li Sze Chow, Martyn Nigel James Paley, Simon J. Hickman:
Evaluation of optimal interpolation and segmentation of the optic nerves on magnetic resonance images for cross-sectional area measurement. Int. J. Imaging Syst. Technol. 34(2) (2024) - Ngangbam Herojit Singh, N. R. Gladiss Merlin, R. Thandaiah Prabu, Deepak Gupta, Meshal Alharbi:
Multi-classification of brain tumor by using deep convolutional neural network model in magnetic resonance imaging images. Int. J. Imaging Syst. Technol. 34(1) (2024) - Talha Iqbal, Aaleen Khalid, Ihsan Ullah:
Explaining decisions of a light-weight deep neural network for real-time coronary artery disease classification in magnetic resonance imaging. J. Real Time Image Process. 21(2): 31 (2024) - Helena R. Torres, Bruno Oliveira, Pedro Morais, Anne Fritze, Gabriele Hahn, Mario Rüdiger, Jaime C. Fonseca, João L. Vilaça:
Infant head and brain segmentation from magnetic resonance images using fusion-based deep learning strategies. Multim. Syst. 30(2): 71 (2024) - Kefan Li, Baozhu Qi, Mingjia Wang:
Magnetic resonance image segmentation of rectal tumors based on improved CycleGAN and U-Net models. Multim. Tools Appl. 83(11): 33555-33571 (2024) - Ishwari Singh Rajput, Aditya Gupta, Vibha Jain, Sonam Tyagi:
A transfer learning-based brain tumor classification using magnetic resonance images. Multim. Tools Appl. 83(7): 20487-20506 (2024) - B. Ramu, Sandeep Bansal:
Highly accurate tumour region segmentation from magnetic resonance images using customized convolutional neural networks. Multim. Tools Appl. 83(5): 14423-14445 (2024) - B. Ramu, Sandeep Bansal:
Correction to: Highly accurate tumour region segmentation from magnetic resonance images using customized convolutional neural networks. Multim. Tools Appl. 83(5): 14447 (2024) - Shubhangi Solanki, Uday Pratap Singh, Siddharth Singh Chouhan, Sanjeev Jain:
A systematic analysis of magnetic resonance images and deep learning methods used for diagnosis of brain tumor. Multim. Tools Appl. 83(8): 23929-23966 (2024) - Bindu Puthentharayil Vikraman, A. Jabeena:
Segmentation based medical image compression of brain magnetic resonance images using optimized convolutional neural network. Multim. Tools Appl. 83(9): 26643-26661 (2024) - Georgina Waldo-Benítez, Luis Carlos Padierna, Pablo Ceron, Modesto A. Sosa:
Dementia classification from magnetic resonance images by machine learning. Neural Comput. Appl. 36(6): 2653-2664 (2024) - R. Pitchai, P. Supraja, A. Helen Victoria, M. Madhavi:
Retraction Note: Brain Tumor Segmentation Using Deep Learning and Fuzzy K-Means Clustering for Magnetic Resonance Images. Neural Process. Lett. 56(2): 137 (2024) - Md. Biddut Hossain, Rupali Kiran Shinde, Sukhoon Oh, Ki-Chul Kwon, Nam Kim:
A Systematic Review and Identification of the Challenges of Deep Learning Techniques for Undersampled Magnetic Resonance Image Reconstruction. Sensors 24(3): 753 (2024) - A. Padmanabha Sarma, G. Saranya:
Segmentation of the Corpus Callosum from Brain Magnetic Resonance Images Using Dual Deep Learning Classifiers and Optimized U-Shaped Neural Networks. SN Comput. Sci. 5(1): 1 (2024) - Chandan Singh, Sukhjeet Kaur Ranade, Dalvinder Kaur, Anu Bala:
A kernelized-bias-corrected fuzzy C-means approach with moment domain filtering for segmenting brain magnetic resonance images. Soft Comput. 28(3): 1909-1933 (2024) - Jonghun Kim, Hyunjin Park:
Adaptive Latent Diffusion Model for 3D Medical Image to Image Translation: Multi-modal Magnetic Resonance Imaging Study. WACV 2024: 7589-7598 - Yidong Zhao, Yi Zhang, Qian Tao:
Relaxometry Guided Quantitative Cardiac Magnetic Resonance Image Reconstruction. CoRR abs/2403.00549 (2024) - 2023
- Gökhan Uçar:
Beyaz cevher hiperintensitelerinin derin öğrenme teknikleri kullanılarak beyin manyetik rezonans görüntülerinden otomatik tespiti (Automatic detection of white matter hyperintensities using deep learning techniques on brain magnetic resonance images). Bilecik Şeyh Edebali University, Turkey, 2023 - Xunan Huang, Bo Pang, Tao Zhang, Guang Jia, Ying Wang, Yonglin Li:
Improved Prostate Biparameter Magnetic Resonance Image Segmentation Based on Def-UNet. IEEE Access 11: 43089-43100 (2023) - Sergey Kastryulin, Jamil Zakirov, Nicola Pezzotti, Dmitry V. Dylov:
Image Quality Assessment for Magnetic Resonance Imaging. IEEE Access 11: 14154-14168 (2023) - Sifa Özsari, Fatima Rabia Yapicioglu, Dilek Yilmaz, Kivanç Kamburoglu, Mehmet Serdar Güzel, Gazi Erkan Bostanci, Koray Açici, Tunç Asuroglu:
Interpretation of Magnetic Resonance Images of Temporomandibular Joint Disorders by Using Deep Learning. IEEE Access 11: 49102-49113 (2023) - R. Preetha, M. Jasmine Pemeena Priyadarsini, Nisha J. S.:
Comparative Study on Architecture of Deep Neural Networks for Segmentation of Brain Tumor using Magnetic Resonance Images. IEEE Access 11: 138549-138567 (2023)
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