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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. (link to thesis)

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.

QIN

TCGA_RCC

TCIA DOI

Publications relating to specific data collections:

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