Microvessel prediction in H&E Stained Pathology Images using fully convolutional neural networks.

Journal: BMC bioinformatics
Published Date: Feb 27, 2018

Abstract

BACKGROUND: Pathological angiogenesis has been identified in many malignancies as a potential prognostic factor and target for therapy. In most cases, angiogenic analysis is based on the measurement of microvessel density (MVD) detected by immunostaining of CD31 or CD34. However, most retrievable public data is generally composed of Hematoxylin and Eosin (H&E)-stained pathology images, for which is difficult to get the corresponding immunohistochemistry images. The role of microvessels in H&E stained images has not been widely studied due to their complexity and heterogeneity. Furthermore, identifying microvessels manually for study is a labor-intensive task for pathologists, with high inter- and intra-observer variation. Therefore, it is important to develop automated microvessel-detection algorithms in H&E stained pathology images for clinical association analysis.

Authors

  • Faliu Yi
    Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, 5325 Harry Hines Blvd, Dallas, TX, 75390, USA.
  • Lin Yang
    National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China.
  • Shidan Wang
    Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, 5325 Harry Hines Blvd, Dallas, TX, 75390, USA.
  • Lei Guo
    Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Chenglong Huang
    Colleyville Heritage High School, Colleyville, TX, 76034, USA, ²Highland Park High School, Dallas, TX, 75205, USA, ³Department of Clinical Science, The University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
  • Yang Xie
    Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, 5325 Harry Hines Blvd, Dallas, TX, 75390, USA.
  • Guanghua Xiao

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