Similarity measurement of lung masses for medical image retrieval using kernel based semisupervised distance metric.

Journal: Medical physics
Published Date: Dec 1, 2016

Abstract

PURPOSE: To develop a new algorithm to measure the similarity between the query lung mass and reference lung mass data set for content-based medical image retrieval (CBMIR).

Authors

  • Guohui Wei
    Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang 110819, China.
  • He Ma
    Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang 110819, China and Key Laboratory of Medical Image Computing, Ministry of Education, Northeastern University, Shenyang 110819, China.
  • Wei Qian
    Department of Electrical and Computer Engineering, University of Texas at El Paso, 500 West University Avenue, El Paso, TX 79968, USA; Sino-Dutch Biomedical and Information Engineering School, Northeastern University, No.11, Lane 3, Wenhua Road, Heping District, Shenyang, Liaoning 110819, China. Electronic address: wqian@utep.edu.
  • Min Qiu
    Affiliated Hospital of Jining Medical University, Jining 272029, China.

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