[19] |
赵旭,王宏.基于Mask RCNN改进的全自动脑肿瘤分割[J].首都师范大学学报(自然科学版), 2021,42(6): 1-7.
|
[20] |
叶德湫,许淑惠,黄永础,等.桥小脑角区肿瘤的MRI诊断价值[J].中外医学研究, 2017, 15(1): 50-51.
|
[21] |
陈琪,李国强,李惊涛. MRI对颅内脑膜瘤的诊断价值研究[J].中国CT和MRI杂志, 2016, 14(4): 23-26.
|
[22] |
刘颖,陈静聪,胡小洋,等.基于Mask RCNN的桥小脑角区脑膜瘤与听神经瘤分类定位研究[J].波谱学杂志, 2021, 38(1): 58-68.
|
[23] |
刘颖,郭伊云,陈静聪,等.基于Faster-RCNN和Level-Set的桥小脑角区肿瘤自动精准分割[J].波谱学杂志, 2021, 38(3): 381-391.
|
[24] |
刘大鹏,程君,黄唯,等.增强的基于灰度共生矩阵的脑肿瘤MRI图像分类[J].中国医学物理学杂志, 2015, 32(6): 772-776.
|
[25] |
Masood M, Nazir T, Nawaz M, et al. A novel deep learning method for recognition and classification of brain tumors from MRI images[J]. Diagnostics (Basel), 2021, 11(5): 744.
|
[26] |
Huang G, Liu Z, Van Der Maaten L, et al. Densely connected convolutional networks[C]//2017 IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, 2017: 2261-2269.
|
[27] |
Lee MKI, Rabindranath M, Faust K, et al. Compound computer vision workflow for efficient and automated immunohistochemical analysis of whole slide images[J]. J Clin Pathol, 2022, online ahead of print.
|
[28] |
Yoon HG, Cheon W, Jeong SW, et al. Multi-parametric deep learning model for prediction of overall survival after postoperative concurrent chemoradiotherapy in glioblastoma patients[J]. Cancers (Basel), 2020, 12(8): 2284.
|
[1] |
Krizhevsky A, Sutskever I, Hinton GE. ImageNet classification with deep convolutional neural networks[C]//Advances in neural information processing systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. La Jolla, CA: Neural Information Processing Systems, 2012: 1097-1105.
|
[2] |
He J, Baxter SL, Xu J, et al. The practical implementation of artificial intelligence technologies in medicine[J]. Nat Med, 2019, 25(1): 30-36.
|
[3] |
He K, Gkioxari G, Dollar P, et al. Mask R-CNN[J]. IEEE Trans Pattern Anal Mach Intell, 2020, 42(2): 386-397.
|
[4] |
Girshick R, Donahue J, Darrell T, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]//2014 IEEE Conference on Computer Vision and Pattern Recognition, Columbus, 2014: 580-587.
|
[5] |
He K, Zhang X, Ren S, et al. Deep residual learning for image recognition[C]//2016 IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, 2016: 770-778.
|
[6] |
刘阳,谢永强,李忠博,等.基于深度学习的目标检测算法研究进展[J].通信技术, 2021, 54(9): 2063-2073.
|
[7] |
Shelhamer E, Long J, Darrell T. Fully convolutional networks for semantic segmentation[J]. IEEE Trans Pattern Anal Mach Intell, 2017, 39(4): 640-651.
|
[8] |
Ronneberger O, Fischer P, Brox T. U-net: Convolutional networks for biomedical image segmentation[C]//International Conference on Medical image computing and computer-assisted intervention, Berlin: Springer, 2015: 234-241.
|
[9] |
Milletari F, Navab N, Ahmadi SA. V-net: fully convolutional neural networks for volumetric medical image segmentation[C]//Fourth International Conference on 3D Vision, Stanford, 2016: 565-571.
|
[10] |
欧攀,路奎,张正,等.基于Mask RCNN的目标识别与空间定位[J].计算机测量与控制, 2019, 27(6): 172-176.
|
[11] |
张博,周军,王芳,等.基于Mask R-CNN的触摸屏玻璃疵病检测与识别[J].软件导刊, 2019, 18(2): 64-67, 71.
|
[12] |
Thiruppathiraj S, Kumar U, Buchke S. Automatic pothole classification and segmentation using android smartphone sensors and camera images with machine learning techniques[C]//2020 IEEE Region 10 Conference (TENCO), Osaka, 2020: 1386-1391.
|
[13] |
Resente G, Gillert A, Trouillier M, et al. Mask, train, repeat! Artificial intelligence for quantitative wood anatomy[J]. Front Plant Sci, 2021, 12: 767400.
|
[14] |
黄毅鹏,胡冀苏,钱旭升,等. SE-Mask-RCNN:多参数MRI前列腺癌分割方法[J].浙江大学学报(工学版), 2021, 55(1): 203-212.
|
[15] |
Ahammed Muneer KV, Rajendran VR, K PJ. Glioma tumor grade identification using artificial intelligent techniques[J]. J Med Syst, 2019, 43(5): 113.
|
[16] |
Zhuge Y, Ning H, Mathen P, et al. Automated glioma grading on conventional MRI images using deep convolutional neural networks[J]. Med Phys, 2020, 47(7): 3044-3053.
|
[17] |
Choi KS, Choi SH, Jeong B. Prediction of IDH genotype in gliomas with dynamic susceptibility contrast perfusion MR imaging using an explainable recurrent neural network[J]. Neuro Oncol, 2019, 21(9): 1197-1209.
|
[18] |
Jeong J, Lei Y, Kahn S, et al. Brain tumor segmentation using 3D Mask R-CNN for dynamic susceptibility contrast enhanced perfusion imaging[J]. Phys Med Biol, 2020, 65(18): 185009.
|