Detail of the student project

Topic:Analýza 2D ultrazvukových snímků vaječníků
Department:Katedra kybernetiky
Supervisor:prof. Dr. Ing. Jan Kybic
Announce as:Diplomová práce, Semestrální projekt
Description:Compare expert annotations with the number of acquired
follicles. Create a method for detection and segmentation of follicles
and an estimation of their number and size. Experimentally evaluate
the accuracy and compare it with results from the literature

[The student will take care of obtaining the data.]
Bibliography:[1] A. Krivanek and M. Sonka, "Ovarian ultrasound image analysis: follicle segmentation," in IEEE Transactions on Medical Imaging, vol. 17, no. 6, pp. 935-944, Dec. 1998, doi: 10.1109/42.746626.

[2] H. Li et al., "CR-Unet: A Composite Network for Ovary and Follicle Segmentation in Ultrasound Images," in IEEE Journal of Biomedical and Health Informatics, vol. 24, no. 4, pp. 974-983, April 2020, doi: 10.1109/JBHI.2019.2946092.

[3] Goodfellow, Bengio, Courville: "Deep learning". MIT Press, 2016.
Responsible person: Petr Pošík