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1. Albalooshi FA. Self-organizing Approach to Learn a Level-set Function for Object Segmentation in Complex Background Environments. University of Dayton; 2015. (link to thesis)

2. Nabizadeh N. Automated Brain Lesion Detection and Segmentation Using Magnetic Resonance Images. Miami, FL: University of Miami; 2015. (link to thesis)

3. Camlica Z. Image Area Reduction for Efficient Medical Image Retrieval. Waterloo, Ontario, Canada,: University of Waterloo; 2015. (link to thesis)

4. Hunter L. Radiomics of NSCLC: Quantitative CT Image Feature Characterization and Tumor Shrinkage Prediction. Thesis, University of Texas; 2013.  (link to thesis)

5. Karnayana PM. Radiogenomic correlation for prognosis in patients with glioblastoma multiformae. San Diego State University; 2013. (link to thesis)

6. Nabizadeh, N. Automated Brain Lesion Detection and Segmentation Using Magnetic Resonance Images. Electrical and Computer Engineering. Miami, FL, University of Miami. PhD., 2015.

7. Wieser, H.-P.  Supervised Machine Learning Approach Utilizing Artificial Neural Networks for Automated Prostate Zone Segmentation in Abdominal MR images. Klagenfurt, Austria, Fachhochschule Kärnten/Carinthia University of Applied Sciences; 2013.

Publications relating to specific data collections:

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