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Implement of Semi-Automated Detection of Breast Mass Spiculation Using Active Contour

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Medical-Image-Processing-Final-Project

Implement of Semi-Automated Detection of Breast Mass Spiculation Using Active Contour

Environment

Qt 5.5 (Visual Studio 2013) + OpenCV 3.0

Dataset

http://marathon.csee.usf.edu/Mammography/Database.html

  1. C_0013_1.RIGHT_MLO
  2. B_3084_1.RIGHT_MLO
  3. B_3010_1.RIGHT_MLO
  4. B_3071_1.LEFT_MLO
  5. B_3021_1.LEFT_MLO
  6. B_3017_1.LEFT_MLO

Reference

  1. Boonthong, P., Jantarakongkul, B., Rasmequan, S., Rodtook, A., Chinnasarn, K. (2014). Semi-Automated Detection of Breast Mass Spiculation Using Active Contour. Asia-Pacific Signal and Information Processing Association, 2014 Annual Summit and Conference (APSIPA). Available at: https://www.researchgate.net/publication/234838692_Hill-climbing_Algorithm_for_Efficient_Color-based_Image_Segmentation
  2. Hill-climbing Algorithm for Efficient Color-based Image Segmentation
  3. OpenCV Documentation. Available at: http://docs.opencv.org/
  4. Fuzzy c-means clustering. Available at: https://github.com/shingt/FuzzyCMeans
  5. Active Contour Model based on GVF. Available at: https://github.com/HiDiYANG/ActiveContour
  6. University of South Florida Digital Mammography Home Page. Available at: http://marathon.csee.usf.edu/Mammography/Database.html
  7. LJPEG to PNG Utility. Available at: http://stackoverflow.com/questions/13365587/getting-data-from-digital-database-for-screening-mammography-ddsm

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Implement of Semi-Automated Detection of Breast Mass Spiculation Using Active Contour

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