Deep Semantics-Preserving Hashing Based Skin Lesion Image Retrieval

  • Xiaorong PuEmail author
  • Yan Li
  • Hang Qiu
  • Yinhui Sun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10262)


This study proposes a content-based pigmented skin lesion image retrieval scheme on semantic hash clustering on the output of the deep neural networks. The skin lesion images are acquired with standard digital cameras or mobile phones. To retrieval skin lesion images efficiently online, semi-supervised deep convolutional neural network incorporated with hash functions jointly learn feature representations, for preserving similar semantics between skin lesion images, and mappings to hash codes. The target candidates are clustered by Affinity Propagation (AP) for ranking, which are selected among the outputs of layer F7 based on the Hamming distance of their semantic hash codes. Experiments on 4 disease categories of pigmented skin lesions of a set of 239 images yielded a specificity of 93.4% and a sensitivity of 80.89%.


Semantics hash coding Pigmented skin lesion Image retrieval Affinity propagation cluster 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Provincial Key Laboratory of Digital Media, Health Big Data Science Research Center, Big Data Research Center, School of Computer Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengduPeople’s Republic of China

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