Diploma and Master Theses (authored and supervised):

C. Hirsch:
"Automatic Breast Lesion Examination of DCE-MRI Data Based on Fourier Analysis";
Supervisor: E. Gröller, G. Mistelbauer; Institut für Computergraphik und Algorithmen, 2015.

English abstract:
Breast cancer is the second most common cancer death among women in developed countries. In less developed countries it has a mortality rate of about 25% rendering it the most common cancer death. It has been demonstrated that an early breast cancer diagnosis significantly reduces the mortality. In addition to mammography and breast ultrasound, Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is the modality with the highest sensitivity for breast cancer detection. However, systems for automatic lesion analysis are scarce. This thesis proposes a method for lesion evaluation without the necessity of tumor segmentation. The observer has to define a Region Of Interest (ROI) covering the lesion in question and the proposed system performs an automated lesion inspection by computing its Fourier transform. Using the Fourier transformed volume we compute the inertia tensor of its magnitude. Based on the gathered information, the Göttinger score, which is a common breast cancer analysis scheme, is computed and the features are presented in newly create plots. These plots are evaluated with a survey where radiologists participated. The Göttinger score assigns a numeric value for the following features: shape, boundary, Internal Enhancement Characteristics (IEC), Initial Signal Increase (ISI) and Post Initial Signal (PIS). We tested our method on 22 breast tumors (14 malignant and 8 benign ones). Subsequently, we compared our results to the classification of an experienced radiologist. The automatic boundary classification has an accuracy of 0.818, the shape 0.773 and the IEC 0.886 compared to the radiologistīs results. An evaluation of the accuracy of the benign vs. malignant classification shows that the method has an accuracy of 0.682 for all the Göttinger score features and 0.772 using only the shape, boundary and IEC. The evaluation of the plot shows that radiologist like the visual representation of the Göttinger score for single lesions, they, however, refuse the plots where multiple lesions are presented in one visual representation.

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.