Gerda Bortsova is a PhD student at Erasmus Medical Center (Rotterdam, the Netherlands). The topic of her project is “Weakly Labeled Deep Learning for Medical Image Analysis”.
Gerda received a BSc degree in information systems (with distinction) from Kazakh-British Technical University (Almaty, Kazakhstan) in 2014 and an MSc degree in informatics (with highest distinction) from Technical University of Munich (TUM) in 2017. The main focus of her Master’s program was computer vision, machine learning and artificial intelligence. As a part of her studies, she was involved in several projects on development of novel machine learning algorithms for biomedical image analysis under supervision of Prof. Dr. Nassir Navab (Computer Aided Medical Procedures, TUM) and Dr. Marleen de Bruijne (BIGR, Erasmus MC).
- Bortsova, G., van Tulder, G., Dubost, F., Peng, T., Navab, N., van der Lugt, A., … de Bruijne, M. (2017). Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks. In International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer.
- Bortsova, G., Sterr, M., Wang, L., Milletari, F., Navab, N., Böttcher, A., … Peng, T. (2016). Mitosis Detection in Intestinal Crypt Images with Hough Forest and Conditional Random Fields. In International Workshop on Machine Learning in Medical Imaging (pp. 287–295). Springer.