Yasser Mostafa Kadah

Professor of Biomedical Engineering

Advanced Topics in Biomedical Engineering I


Important Information:  Term Grades

Main Theme

Computer Aided Diagnosis in Digital Mammography


  • Evidence Based Radiology

  • Diagnostic Performance Assessment

  • Computer Aided Detection and Diagnosis

  • Preprocessing and Normalization

  • Feature Extraction Strategies

  • Feature Selection Strategies

  • Classification Strategies

  • Advanced Topics



Data Sets

  • The mini-MIAS data set (copy on my web site)

  • DDSM Mammography Database LJPEG Reading instructions:

    1. Download the open-source PVRG code for decompressing LJPEG images (working copy available on my site here that produces a raw image and a text file containing the size information to be used by Octave or Matlab to read the raw image file. To compile under Linux, just decompress and change directory to inside the folder and from the command line "make". Please note that the compiled binary named "jpeg" obtained for Ubuntu v. 11.10 is available in this directory and can be used directly)

    2. Convert the LJPEG images into raw images using this commmand as in the following example: 
      $ ./jpeg -d -s  A_1108_1.LEFT_CC.LJPEG  

    3. Read in the output raw data file "A_1108_1.LEFT_CC.LJPEG.1" with image height (GH) and width (GW) provided in the text file under the name  "A_1108_1.LEFT_CC.LJPEG.txt"  using the following code for Octave/Matlab:        
      fid = fopen('h:\C_0018_1.LEFT_CC.LJPEG.1','r','ieee-be');
      image = fread(fid,[ GH  , GW],'short');
      image = image';
      image = uint16(image);
      imshow(image)     %works with Octave to display whole image
      imagesc(image)        % works with Matlab to display whole image








More Information

Please follow the links here to download course material