液晶与显示, 2020, 35 (6): 619, 网络出版: 2020-10-27   

多视角判别度量学习的乳腺影像检索方法

Multi-view metric learning with Fisher discriminant analysis and
作者单位
1 常州工业职业技术学院 信息工程系, 江苏 常州 213164
2 扬州大学 信息工程学院, 江苏 扬州 225127
3 常州大学 信息科学与工程学院, 江苏 常州 213164
引用该论文

周国华, 蒋晖, 顾晓清, 殷新春. 多视角判别度量学习的乳腺影像检索方法[J]. 液晶与显示, 2020, 35(6): 619.

ZHOU Guo-hua, JIANG Hui, GU Xiao-qing, YIN Xin-chun. Multi-view metric learning with Fisher discriminant analysis and[J]. Chinese Journal of Liquid Crystals and Displays, 2020, 35(6): 619.

参考文献

[1] 何明艳, 朱碧琪, 钟媛, 等.2005-2013年中国女性乳腺癌发病及死亡趋势分析[J].中华疾病控制杂志, 2019, 23(1): 10-14.

    HE M Y, ZHU B Q, ZHONG Y, et al. Analysis of the incidence and mortality trend of breast cancer in Chinese women from 2005 to 2013 [J]. Chinese Journal of Disease Control & Prevention, 2019, 23(1): 10-14. (in Chinese)

[2] 丁冠宇, 杜宝吉, 韩旭, 等. 功能化金纳米星作为药物载体用于乳腺癌光热和化疗的协同治疗研究 [J]. 分析化学, 2018, 46(8): 1193-1200.

    DING G Y, DU J, HAN X, et al. Functionalized gold nano-stars as chemotherapeutic drugs vector for chemo-and photothermal synergistic therapy of breast cancer [J]. Chinese Journal of Analytical Chemistry, 2018, 46(8): 1193-1200. (in Chinese)

[3] 王振召, 魏斌斌, 陈峥, 等. 基于核磁共振技术的临床尿毒症的代谢组学研究 [J]. 分析化学, 2018, 46(9): 1415-1423.

    WANG Z Z, WEI B B, CHEN Z, et al. 1H nuclear magnetic resonance-based investigation of uremia by metabolomic analysis [J]. Chinese Journal of Analytical Chemistry, 2018, 46(9): 1415-1423.. (in Chinese)

[4] 张天琪, 韩雪立, 何洋洋, 等. 聚乙二醇修饰氧化钨纳米探针的合成及用于胃肠道CT成像 [J]. 分析化学, 2018, 46(10): 1539-1544.

    ZHANG T Q, HAN X L, HE Y Y, et al. Facile synthesis of PEGylated tungsten-based nanoprobes for gastric computed tomography imaging [J]. Chinese Journal of Analytical Chemistry, 2018, 46(10): 1539-1544. (in Chinese)

[5] SOMASHEKHAR S P, SEPLVEDA M J, PUGLIELLI S, et al. Watson for oncology and breast cancer treatment recommendations: agreement with an expert multidisciplinary tumor board [J]. Annals of Oncology, 2018, 29(2): 418-423.

[6] 周蕾.多视角乳腺医学影像案例检索技术的研究[D].哈尔滨: 哈尔滨理工大学, 2013.

    ZHOU L. Research on techniques of multi-angle medical image retrieval [D]. Harbin: Harbin University of Science and Technology, 2013. (in Chinese)

[7] GU D X, LIANG C Y, ZHAO H M. A case-based reasoning system based on weighted heterogeneous value distance metric for breast cancer diagnosis [J]. Artificial Intelligence in Medicine, 2017, 77: 31-47.

[8] 龚敬, 郝雯, 彭卫军.人工智能技术在乳腺影像学诊断中的应用现状与展望[J].肿瘤影像学, 2019, 28(3): 134-138.

    GONG J, HAO W, PENG W J. Application and prospect of artificial intelligence in breast imaging diagnosis [J]. Oncoradiology, 2019, 28(3): 134-138. (in Chinese)

[9] LAMY J B, SEKAR B, GUEZENNEC G, et al. Explainable artificial intelligence for breast cancer: a visual case-based reasoning approach [J]. Artificial Intelligence in Medicine, 2019, 94: 42-53.

[10] 吴磊, 吕国强, 赵晨, 等.基于多尺度残差网络的CT图像超分辨率重建[J].液晶与显示, 2019, 34(10): 1006-1012.

    WU L, LYU G Q, ZHAO C, et al. CT image super-resolution reconstruction based on multi-scale residual network [J]. Chinese Journal of Liquid Crystals and Displays, 2019, 34(10): 1006-1012. (in Chinese)

[11] 魏国辉, 齐守良, 钱唯, 等.基于相似性度量的肺结节图像检索算法[J].东北大学学报: 自然科学版, 2018, 39(9): 1226-1231.

    WEI G H, QI S L, QIAN W, et al. Image retrieval algorithm of pulmonary nodules based on similarity measurement [J]. Journal of Northeastern University: Natural Science, 2018, 39(9): 1226-1231. (in Chinese)

[12] SUN S L. A survey of multi-view machine learning [J]. Neural Computing and Applications, 2013, 23(7): 2031-2038.

[13] SHEN H L, ZHAO Y W, MA D F, et al. Query dependent multiview features fusion for effective medical image retrieval [C]//Proceedings of 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). Wuhan, China: IEEE, 2014.

[14] SHEN H L, TAO D C, MA D F. Multiview locally linear embedding for effective medical image retrieval [J]. PLoS One, 2013, 8(12): e82409.

[15] DAS R, THEPADE S, GHOSH S. Framework for content-based image identification with standardized multiview features [J]. ETRI Journal, 2016, 38(1): 174-184.

[16] MOURA D C, LPEZ M A G. An evaluation of image descriptors combined with clinical data for breast cancer diagnosis [J]. International Journal of Computer Assisted Radiology and Surgery, 2013, 8(4): 561-574.

[17] 毛金莲.自适应多视角学习及其在图像分类中的应用[J].计算机应用, 2013, 33(7): 1955-1959.

    MAO J L. Adaptive multi-view learning and its application to image classification [J]. Journal of Computer Applications, 2013, 33(7): 1955-1959. (in Chinese)

[18] HUANG C Q, CHUNG F L, WANG S T. Multi-view L2-SVM and its multi-view core vector machine [J]. Neural Networks, 2016, 75: 110-125.

[19] ZHU C M, WANG Z, GAO D Q. New design goal of a classifier: global and local structural risk minimization [J]. Knowledge-Based Systems, 2016, 100: 25-49.

[20] WANG Z, ZHU Y J, LIU W W, et al. Multi-view learning with Universum [J]. Knowledge-Based Systems, 2014, 70: 376-391.

[21] 陈静 张静. 改进高斯过程回归的高光谱空谱联合分类算法 [J]. 光学 精密工程, 2019, 27(7): 1649-1660.

    CHEN J, ZHANG J. Spectral-spatial joint classification of hyperspectral image algorithm based on improved gaussian process regression [J]. Optics and Precision Engineering, 2019, 27(7): 1649-1660. (in Chinese)

[22] 吕鹏飞 陆志谦 何巧芝 等. 基于光声谱法的无创血糖在体检测初探 [J]. 光学 精密工程, 2019, 27(6): 1301-1308.

    LYU P F, LU Z Q, HE Q Z, et al. Non-invasive blood glucose in vivo detection based on photoacoustic spectroscopy [J]. Optics and Precision Engineering, 2019, 27(6): 1301-1308. (in Chinese)

[23] 高赟 赵江珊 罗久桓 等. 采用响应图置信区域自适应特征融合的相关滤波跟踪 [J]. 光学 精密工程, 2019, 27(5): 1178-1187.

    GAO Y, ZHAO J S, LUO J H, et al. Adaptive feature fusion with confidence region of response map for correlation filter tracker [J]. Optics and Precision Engineering, 2019, 27(5): 1178-1187. (in Chinese)

[24] 吕晓琪, 吴凉, 谷宇, 等. 基于三维卷积神经网络的低剂量CT肺结节检测 [J]. 光学 精密工程, 2018, 26(5): 1211-1218. LYU X Q, WU L, GU Y, et al. Detection of low dose CT pulmonary nodules based on 3D convolution neural network [J]. Optics and Precision Engineering, 2018, 26(5): 1211-1218. (in Chinese)

[25] 吴其平,吴成茂. 快速鲁棒核空间模糊聚类分割[J].中国图象图形学报, 2018, 23(12): 1838-1851.

    WU Q P, WU C M. Fast robust kernel-based fuzzy C-means clustering segmentation [J]. Journal of Image and Graphics, 2018, 23(12): 1838-1851. (in Chinese)

[26] 李婷婷,江朝晖,饶元,等. 结合基因表达式编程与空间模糊聚类的图像分割 [J].中国图象图形学报, 2017, 22(5): 575-583.

    LI T T, JIANG Z H, RAO Y, et al. XiaomingImage segmentation based on gene expression programming and spatial fuzzy clustering [J]. Journal of Image and Graphics, 2017, 22(5): 575-583. (in Chinese)

[27] 崔西希,吴成茂. 核空间中智模糊聚类及图像分割应用 [J].中国图象图形学报, 2016, 21(10): 1316-1327,

    CUI X X, WU C M. Neutrosophic C-means clustering in kernel space and its application in image segmentation [J]. Journal of Image and Graphics, 2016, 21(10): 1316-1327, (in Chinese)

周国华, 蒋晖, 顾晓清, 殷新春. 多视角判别度量学习的乳腺影像检索方法[J]. 液晶与显示, 2020, 35(6): 619. ZHOU Guo-hua, JIANG Hui, GU Xiao-qing, YIN Xin-chun. Multi-view metric learning with Fisher discriminant analysis and[J]. Chinese Journal of Liquid Crystals and Displays, 2020, 35(6): 619.

本文已被 2 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!