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Order-Sensitive Deep Hashing for Multimorbidity Medical Image Retrieval

  • Zhixiang Chen
  • Ruojin Cai
  • Jiwen LuEmail author
  • Jianjiang Feng
  • Jie Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11070)

Abstract

In this paper, we propose an order-sensitive deep hashing for scalable medical image retrieval in the scenario of coexistence of multiple medical conditions. The pairwise similarity preservation in existing hashing methods is not suitable for this multimorbidity medical image retrieval problem. To capture the multilevel semantic similarity, we formulate it as a multi-label hashing learning problem. We design a deep hash model for powerful feature extraction and preserve the ranking list with a triplet based ranking loss for better assessment assistance. We further introduce the cross-entropy based multi-label classification loss to exploit multi-label information. We solve the optimization problem by continuation to reduce the quantization loss. We conduct extensive experiments on a large database constructed on the NIH Chest X-ray database to validate the efficacy of the proposed algorithm. Experimental results demonstrate that our order sensitive deep hashing leads to superior performance compared with several state-of-the-art hashing methods.

Notes

Acknowledgment

This work was supported in part by the National Key Research and Development Program of China under Grant 2017YFA0700802, the National Natural Science Foundation of China under Grants 61672306, U1713214, 61572271, and 61527808, the National 1000 Young Talents Plan Program, the National Postdoctoral Program for Innovative Talents under Grant BX201700137, China Postdoctoral Science Foundation under Grant 2018M630159, Tsinghua University Initiative Scientific Research Program.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Zhixiang Chen
    • 1
    • 2
    • 3
  • Ruojin Cai
    • 1
  • Jiwen Lu
    • 1
    • 2
    • 3
    Email author
  • Jianjiang Feng
    • 1
    • 2
    • 3
  • Jie Zhou
    • 1
    • 2
    • 3
  1. 1.Department of AutomationTsinghua UniversityBeijingChina
  2. 2.State Key Lab of Intelligent Technologies and SystemsTsinghua UniversityBeijingChina
  3. 3.Beijing National Research Center for Information Science and TechnologyBeijingChina

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