·864· 智能系统学报 第12卷 1nc.2000:518-529 Diego,USA,2016:97850Q [6]WEISS Y,TORRALBA A,FERGUS R.Spectral Hashing [16]BABENKO,SLESAREV A,CHIGORIN A,et al.Neural [J.Proc nips.2008,282(3):1753-1760. codes for image retrieval[M].Springer International Pub- [7]GONG Y,LAZEBNIK S,GORDO A,et al.Iterative quant- lishing.2014:584599. ization:a procrustean approach to learning binary codes for [17]FU H,KONG X,WANG Z.Binary code reranking meth- large-scale image retrieval[J].IEEE transactions on pattern od with weighted hamming distance[J].Multimedia tools analysis and machine intelligence,2013,35(12):2916-29. and applications,2016,75(3):1391-1408. [8]LIU W,WANG J,JI R,et al.Supervised hashing with ker- [18]王超,王浩,王伟,等.基于优化ROI的医学图像分割与压 nels[C]//2012 IEEE Conference on Computer Vision and 缩方法研究[.重庆邮电大学学报:自然科学版,2015 Pattern Recognition(CVPR).Providence,USA,2012: 27(2):279-284 2074-2081 WANG Chao,WANG Hao,WANG Wei,et al.Study of [9]JING M,ZHANG S,HUANG J,et al.Joint kerel-based su- optimized ROI based medical image segmentation and pervised hashing for scalable histopathological image ana- compression method[J].Journal of Chongqing university lysis[C]//Medical Image Computing and Computer-As- of posts and telecommunications:natural science edition, sisted Intervention 2015.Springer International Publishing. 2015,27(2):279-284 2015.1:558-560. [19]LIAO X,ZHAO J,CHENG J,et al.A segmentation meth- [10]LIU J,ZHANG S,LIU W,et al.Scalable mammogram re- od for lung parenchyma image sequences based on super- trieval using composite anchor graph hashing with iterat- pixels and a self-generating neural forest[J].Plos one, ive quantization[J].IEEE transactions on circuits and sys- 2016,11(8):e0160556 tems for video technology,2016(99):1-1. [11]LIU H M,WANG R P,SHAN S,et al.Deep supervised 作者简介: hashing for fast image retrieval[C]//Proceedings of Interna- 杨晓兰,女,1991年生,硕士研究 tional Conference on Computer Vision and Pattern Recog- 生,主要研究方向为图像处理与图像 检索。 nition(CVPR).Las Vegas,USA,2016:2064-2072. [12]YANG H F,LIN K,CHEN C S.Supervised learning of se- mantics-preserving hash via deep convolutional neural net- works[J].IEEE transactions on pattern analysis and ma- chine intelligence,2015(99):1-1. 强彦,男,1969年生,教授,博士 [13]ARMATO S,MCLENNAN G,MCNITTt-GRAY M.et al. 生导师,博士,主要研究方向为图像处 WEB201B02:the lung image database consortium(LIDC) 理、云计算、大数据。主持参与国家自 and image database resource initiative (IDRI):a completed 然科学基金、虚拟现实技术与系统国 public database of CT scans for lung nodule analysis[J]. 家重点实验室开放基金等项目。 Medical physics,2010,37(6):3416-3417. [14]YANG X,CHENG K T.Local difference binary for ultra- fast and distinctive feature description[J].IEEE transac- 赵涓涓,女,1975年生,教授,博 tions on pattern analysis and machine intelligence,2014, 士生导师,博士,主要研究方向为图像 处理、模式识别、深度学习。主持参与 36(1188-94. 国家自然科学基金、山西省回国留学 [15]TARANDO S R,FETITA C.Increasing CAD system ef- 人员科研资助项目等项目。 ficacy for lung texture analysis using a convolutional net- work[Cl//Proceedings of SPIE 9785,Medical Imaging.SanInc. 2000: 518–529. WEISS Y, TORRALBA A, FERGUS R. Spectral Hashing [J]. Proc nips, 2008, 282(3): 1753–1760. [6] GONG Y, LAZEBNIK S, GORDO A, et al. Iterative quantization: a procrustean approach to learning binary codes for large-scale image retrieval[J]. IEEE transactions on pattern analysis and machine intelligence, 2013, 35(12): 2916–29. [7] LIU W, WANG J, JI R, et al. Supervised hashing with kernels[C]//2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Providence, USA, 2012: 2074–2081. [8] JING M, ZHANG S, HUANG J, et al. Joint kernel-based supervised hashing for scalable histopathological image analysis[C]//Medical Image Computing and Computer-Assisted Intervention 2015. Springer International Publishing, 2015, 1: 558–560. [9] LIU J, ZHANG S, LIU W, et al. Scalable mammogram retrieval using composite anchor graph hashing with iterative quantization[J]. IEEE transactions on circuits and systems for video technology, 2016(99): 1–1. [10] LIU H M, WANG R P, SHAN S, et al. Deep supervised hashing for fast image retrieval[C]//Proceedings of International Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas, USA, 2016: 2064–2072. [11] YANG H F, LIN K, CHEN C S. Supervised learning of semantics-preserving hash via deep convolutional neural networks[J]. IEEE transactions on pattern analysis and machine intelligence, 2015(99): 1–1. [12] ARMATO S, MCLENNAN G, MCNITTt-GRAY M, et al. WEB201B02: the lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed public database of CT scans for lung nodule analysis[J]. Medical physics, 2010, 37(6): 3416–3417. [13] YANG X, CHENG K T. Local difference binary for ultrafast and distinctive feature description[J]. IEEE transactions on pattern analysis and machine intelligence, 2014, 36(1): 188–94. [14] TARANDO S R, FETITA C. Increasing CAD system efficacy for lung texture analysis using a convolutional network[C]//Proceedings of SPIE 9785, Medical Imaging. San [15] Diego, USA, 2016: 97850Q. BABENKO, SLESAREV A, CHIGORIN A, et al. Neural codes for image retrieval[M]. Springer International Publishing, 2014: 584–599. [16] FU H, KONG X, WANG Z. Binary code reranking method with weighted hamming distance[J]. Multimedia tools and applications, 2016, 75(3): 1391–1408. [17] 王超,王浩,王伟,等. 基于优化 ROI 的医学图像分割与压 缩方法研究[J]. 重庆邮电大学学报: 自然科学版, 2015, 27(2): 279–284. WANG Chao, WANG Hao, WANG Wei, et al. Study of optimized ROI based medical image segmentation and compression method[J]. Journal of Chongqing university of posts and telecommunications: natural science edition, 2015, 27(2): 279–284. [18] LIAO X, ZHAO J, CHENG J, et al. A segmentation method for lung parenchyma image sequences based on superpixels and a self-generating neural forest[J]. Plos one, 2016, 11(8): e0160556. [19] 作者简介: 杨晓兰,女,1991 年生,硕士研究 生,主要研究方向为图像处理与图像 检索。 强彦,男,1969 年生,教授,博士 生导师,博士,主要研究方向为图像处 理、云计算、大数据。主持参与国家自 然科学基金、虚拟现实技术与系统国 家重点实验室开放基金等项目。 赵涓涓,女,1975 年生,教授,博 士生导师,博士,主要研究方向为图像 处理、模式识别、深度学习。主持参与 国家自然科学基金、山西省回国留学 人员科研资助项目等项目。 ·864· 智 能 系 统 学 报 第 12 卷