Breast cancer is the most common life-threatening type of cancer affecting women in The Netherlands. The success of the treatment of breast cancer largely depends on the stage of a tumor at the time of detection. Therefore, early detection of breast cancer is essential. Although mammography screening is currently the most effective tool for early detection of breast cancer, up to one-fifth of women with invasive breast cancer have a mammogram that is interpreted as normal, i.e., a false-negative mammogram result. To overcome such limitations, Computer-Aided Diagnosis (CAD) systems for automatic classification of breast lesions as either benign or malignant are being developed. CAD systems help radiologists with the interpretation of lesions, such that they refer less women for further examination when they actually have benign lesions. In this thesis we constructed several types of classifiers, i.e., Bayesian networks and support vector machines, for the task of computer-aided diagnosis of breast lesions.

Classification of Breast Lesions in Digital Mammograms, Master Thesis (1.3 MB PDF)

I spent three weeks visiting the United Arabic Emirates and Oman with a good friend from 20 May to 10 June 2006 arriving in Dubai and travelling to Sharjah, Ajman, Fujairah, Ras al-Khaimah, Umm al-Qaiwan and Abu Dhabi. The second half of our trip took us to the hottest capital of the world: Muscat, Oman. Here is the travel report from day to day, with links to the photos. And the full gallery is here.