과제정보
이 논문은 2021년도 조선대학교 학술연구비의 지원을 받아 연구되었음.
참고문헌
- Statistics on Melanoma skin cancer problem:https://www.cancer.org/research/cancer-factsstatistics/all-cancer-facts-figures/cancer-facts-figures2018.html
- O. Ronneberger, P. Fischer, and T. Brox, "U-Net: Convolutional Networks for Biomedical Image Segmentation," arXiv:1505.04597, 2015. [DOI: 10.1007/978-3-319-24574-4_28]
- R. Mehta and J. Sivaswamy, "M-net: A Convolutional Neural Network for Deep Brain Structure Segmentation," 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), 2017, pp. 437-440. [DOI: 10.1109/ISBI.2017.7950584]
- J. Long, E. Shelhamer, and T. Darrell, "Fully Convolutional Networks for Semantic Segmentation," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 3431-3440. [DOI: 10.1109/CVPR.2015.7298965]
- H. Chen, Y. Qi, X. Yu, L. Dou, Q. Qin, and P.-A. Heng, "DCAN: Dual-Channel Convolutional Attention Network for Automatic Nucleus Segmentation in H&E Stained Images," IEEE Transactions on Medical Imaging, vol. 38, no. 2, pp. 359-370, Feb. 2019. [DOI: 10.1109/TMI.2018.2856806]
- Z. Zhang, X. Wei, Z. Zhao, and W. Qian, "Skin Lesion Segmentation Using Deep Convolutional Neural Networks and a Novel Segmentation Quality Evaluation Method," Journal of Imaging, vol. 6, no. 10, p. 95, Oct. 2020. [DOI: 10.3390/jimaging6100095
- J. Dai, K. He, and J. Sun, "Instance-aware Semantic Segmentation via Multi-task Network Cascades," in CVPR, 2016, pp. 3150-3158. [DOI: 10.1109/CVPR.2016.340]
- R. Girshick, J. Donahue, T. Darrell, and J. Malik, "Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation," in CVPR, 2014, pp. 580 - 587. [DOI: 10.1109/CVPR.2014.81]
- A. Krizhevsky, I. Sutskever, and G. E. Hinton, "ImageNet Classification with Deep Convolutional Neural Networks," in NIPS, 2012, pp. 1097 -1105. [DOI: 10.1145/3065386]
- A. B. Ashrafulla, D. M. Shotton, J. Winn, C. Rother, and A. Criminisi, "Anatomy-specific Classification of Medical Images," in ICCV, 2013, pp. 987 - 994. [DOI: 10.1109/ICCV.2013.129]
- Z. Zhang, X. Wei, Z. Zhao, and W. Qian, "Skin Lesion Segmentation Using Deep Convolutional Neural Networks and a Novel Segmentation Quality Evaluation Method," Journal cf Imaging, vol. 6, no. 10, p. 95, Oct. 2020. [DOI: 10.3390/jimaging6100095]
- P. Vakalopoulou, M. M. Zormpas, N. Giatromanolaki, and D. Visvikis, "Deep Learning for the Segmentation of Head and Neck Organs at Risk: A Review," Medical Physics, vol. 47, no. 5, pp. 2011-2027, May 2020. [DOI: 10.1002/mp.l4078]
- J. Dai, K. He, and J. Sun, "Instance-aware Semantic Segmentation via Multi-task Network Cascades," in CVPR, 2016, pp. 3150-3158. [DOI: 10.1109/CVPR.2016.340]
- R. Girshick, J. Donahue, T. Darrell, and J. Malik, "Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation," in CVPR, 2014, pp. 580 - 587. [DOI: 10.1109/CVPR.2014.81]
- A. Krizhevsky, I. Sutskever, and G. E. Hinton, "ImageNet Classification with Deep Convolutional Neural Networks," in NIPS, 2012, pp. 1097 - 1105.
- Hemandez-Orallo, "The Jaccard Index: A Unifying View of Similarity and Diversity Measures," CoRR, vol. abs/1301.3787, 2013
- Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, vol. 27, no. 8, pp. 1847-1
- Z. Zhou, M. M. R. Siddiquee, N. Tajbakhsh, and J. Liang, 'UNet++: Redesigning Skip Comections to Exploit Multiscale Features in Image Segmentation', arXiv [eess.IV]. 2020.
- L. da F. Costa, 'Further Generalizations of the Jaccard Index', arXiv [cs.LG]. 2021.
- N. Codella et al., 'Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)', arXiv [cs.CV]. 2019.