Deep Learning-Based Lung Medical Image Recognition (2024)

[1] Y. Yang, A. Gilliam, E. B. Ludmir, and K. Roberts, "Exploring the Generalization of Cancer Clinical Trial Eligibility Classifiers Across Diseases," arXiv preprint arXiv:2403.17135, 2024.

[2] Y. Zi, Q. Wang, Z. Gao, X. Cheng, and T. Mei, "Research on the Application of Deep Learning in Medical Image Segmentation and 3D Reconstruction," Academic Journal of Science and Technology, vol. 10, no. 2, pp. 8-12, 2024.

[3] Y. Yang, S. Jayaraj, E. Ludmir, and K. Roberts, "Text Classification of Cancer Clinical Trial Eligibility Criteria," in AMIA Annual Symposium Proceedings, vol. 2023, p. 1304, American Medical Informatics Association, 2023.

[4]S. Lu, Z. Liu, T. Liu, and W. Zhou, "Scaling-up medical vision-and-language representation learning with federated learning," Engineering Applications of Artificial Intelligence, vol. 126, p. 107037, 2023.

[5]K. Li, A. Zhu, W. Zhou, P. Zhao, J. Song, and J. Liu, "Utilizing Deep Learning to Optimize Software Development Processes," arXiv preprint arXiv:2404.13630, 2024.

[6]Y. Zhang, P. Ji, A. Wang, J. Mei, A. Kortylewski, and A. Yuille, "3d-aware neural body fitting for occlusion robust 3d human pose estimation," in Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9399-9410, 2023.

[7]Z. Zhao, H. Yu, C. Lyu, P. Ji, X. Yang, and W. Yang, "Cross-Modal 2D-3D Localization with Single-Modal Query," in IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium, pp. 6171-6174, IEEE, July 2023.

[8]G. Lan, X. Y. Liu, Y. Zhang, and X. Wang, "Communication-efficient federated learning for resource-constrained edge devices," IEEE Transactions on Machine Learning in Communications and Networking, 2023.

[9]A. Zhu, K. Li, T. Wu, P. Zhao, W. Zhou, and B. Hong, "Cross-Task Multi-Branch Vision Transformer for Facial Expression and Mask Wearing Classification," arXiv preprint arXiv:2404.14606, 2024.

[10]J. Jin, H. Xu, P. Ji, and B. Leng, "IMC-NET: Learning Implicit Field with Corner Attention Network for 3D Shape Reconstruction," in 2022 IEEE International Conference on Image Processing (ICIP), pp. 1591-1595, IEEE, October 2022.

[11] T. Xu, H. Yang, and T. Wu, "Advancements in AI for Oncology: Developing an Enhanced YOLOv5-based Cancer Cell Detection System," International Journal of Innovative Research in Computer Science and Technology (IJIRCST), vol. 12, no. 2, pp. 75-80, 2024. [Online]. Available: doi:10.55524/ijircst.2024.12.2.13

[12] S. Dlamini, Y. H. Chen, and C. F. J. Kuo, "Complete fully automatic detection, segmentation and 3D reconstruction of tumor volume for non-small cell lung cancer using YOLOv4 and region-based active contour model," Expert Systems with Applications, vol. 212, p. 118661, 2023.

[13] M. Xiao, Y. Li, X. Yan, M. Gao, and W. Wang, "Convolutional neural network classification of cancer cytopathology images: taking breast cancer as an example," arXiv preprint arXiv:2404.08279, 2024.

[14] A. Zhu, J. Li, and C. Lu, "Pseudo view representation learning for monocular RGB-D human pose and shape estimation," IEEE Signal Processing Letters, vol. 29, pp. 712-716, 2021.

[15] X. Yan, W. Wang, M. Xiao, Y. Li, and M. Gao, "Survival Prediction Across Diverse Cancer Types Using Neural Networks," arXiv preprint arXiv:2404.08713, 2024.

[16] X. S. Wang and B. P. Mann, "Attractor Selection in Nonlinear Energy Harvesting Using Deep Reinforcement Learning," arXiv preprint arXiv:2010.01255, 2020.

[17] C. Szegedy et al., "Going deeper with convolutions," in 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1–9, IEEE, Boston, 2015. doi:10.1109/CVPR.2015.7298594

[18] C. Wang, D. Chen, L. Hao, X. Liu, Y. Zeng, J. Chen, and G. Zhang, "Pulmonary image classification based on inception-v3 transfer learning model," IEEE Access, vol. 7, pp. 146533-146541, 2019.

[19] X. S. Wang, J. D. Turner, and B. P. Mann, "Constrained attractor selection using deep reinforcement learning," Journal of Vibration and Control, vol. 27, no. 5-6, pp. 502-514, 2021.

[20] Q. Ning et al., "Rapid segmentation and sensitive analysis of CRP with paper-based microfluidic device using machine learning," Analytical and Bioanalytical Chemistry, vol. 414, no. 13, pp. 3959-3970, 2022.

[21] J. Yao, T. Wu, and X. Zhang, "Improving depth gradient continuity in transformers: A comparative study on monocular depth estimation with cnn," arXiv preprint arXiv:2308.08333, 2023.

[22] G. Lan, H. Wang, J. Anderson, C. Brinton, and V. Aggarwal, "Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates," Advances in Neural Information Processing Systems, vol. 36, 2024.

[23] S. G. Armato III et al., "Data From LIDC-IDRI," The Cancer Imaging Archive. [Online]. Available: https://doi.org/10.7937/K9/TCIA.2015.LO9QL9SX, 2015.

[24] Y. Li, X. Yan, M. Xiao, W. Wang, and F. Zhang, "Investigation of Creating Accessibility Linked Data Based on Publicly Available Accessibility Datasets," in Proceedings of the 2023 13th International Conference on Communication and Network Security, pp. 77–81, Association for Computing Machinery, 2024.

[25] M. Souto, P. G. Tahoces, S. C. JJ, M. J. Lado, M. Remy-Jardin, J. Remy, and J. J. Vidal, "Automatic detection of pulmonary nodules on computed tomography: a preliminary study," Radiologia, vol. 50, no. 5, pp. 387-392, 2008.

[26] C. H. Lee and J. S. Jwo, "Automatic segmentation for pulmonary nodules in CT images based on multifractal analysis," IET Image Processing, vol. 14, no. 7, pp. 1347-1353, 2020.

Deep Learning-Based Lung Medical Image Recognition (2024)
Top Articles
Latest Posts
Article information

Author: Otha Schamberger

Last Updated:

Views: 6495

Rating: 4.4 / 5 (75 voted)

Reviews: 90% of readers found this page helpful

Author information

Name: Otha Schamberger

Birthday: 1999-08-15

Address: Suite 490 606 Hammes Ferry, Carterhaven, IL 62290

Phone: +8557035444877

Job: Forward IT Agent

Hobby: Fishing, Flying, Jewelry making, Digital arts, Sand art, Parkour, tabletop games

Introduction: My name is Otha Schamberger, I am a vast, good, healthy, cheerful, energetic, gorgeous, magnificent person who loves writing and wants to share my knowledge and understanding with you.