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Building a X-ray Database for Mammography on Vietnamese Patients and automatic Detecting ROI Using Mask-RCNN

  • Nguyen Duc Thang
  • Nguyen Viet Dung
  • Tran Vinh Duc
  • Anh Nguyen
  • Quang H. Nguyen
  • Nguyen Tu Anh
  • Nguyen Ngoc Cuong
  • Le Tuan Linh
  • Bui My Hanh
  • Phan Huy Phu
  • Nguyen Hoang PhuongEmail author
Chapter
  • 4 Downloads
Part of the Studies in Computational Intelligence book series (SCI, volume 899)

Abstract

This paper describes the method of building a X-ray database for Mammography on Vietnamese patients that we collected at Hanoi Medical University Hospital. This dataset has 4664 images (Dicom) corresponding to 1161 standard patients with uniform distribution according to BIRAD from 0 to 5. This paper also presents the method of detecting Region of Interest (ROI) in mammogram based on Mask R-CNN architecture. The method of determining the ROI for accuracy mAP@0.5 = 0.8109 and the accuracy of classification BIRAD levels is 58.44%.

Notes

Acknowledgements

This work is supported by foundation of the research and development contract between Thang Long University and Hanoi Medical University Hospital, Vietnam dated on 27 November, 2018 on “Developing a support system for diagnosis of breast cancer based on X-Ray using Artificial Intelligence”.

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Nguyen Duc Thang
    • 1
  • Nguyen Viet Dung
    • 2
  • Tran Vinh Duc
    • 2
  • Anh Nguyen
    • 3
  • Quang H. Nguyen
    • 2
  • Nguyen Tu Anh
    • 1
  • Nguyen Ngoc Cuong
    • 4
  • Le Tuan Linh
    • 4
  • Bui My Hanh
    • 4
  • Phan Huy Phu
    • 1
  • Nguyen Hoang Phuong
    • 1
    Email author
  1. 1.Thang Long UniversityHanoiVietnam
  2. 2.Hanoi University of Science and TechnologyHanoiVietnam
  3. 3.Auburn UniversityAuburnUSA
  4. 4.Hanoi Medical University HospitalHanoiVietnam

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