Bibliographic description:
Kokshaikyna, Mariia. Polyp detection and segmentation from endoscopy images / Mariia Kokshaikyna; Supervisors: Oles Dobosevych, Mariia Dobko; Ukrainian Catholic University, Faculty of Applied Sciences, Department of Computer Sciences. – Lviv 2022. – 42 p.
Abstract:
Endoscopy is a widely used clinical procedure for the detection of different diseases
in internal gastrointestinal tract’s organs such as the stomach and colon. Modern endoscopes
allow getting high-quality video during the procedure. Computer-assisted
methods might support medical specialists in detecting or segmenting anomaly regions
on the picture. Many datasets are available and methods to detect polyp regions
have been proposed. One kind of task is polyps segmentation on images and
videos. The best results in semantic segmentation of polyps are now achieved with
fully supervised approaches. In this thesis, we describe experiments with CaraNet
model. We checked robustness on cross-validation on several publicly available
datasets and small private dataset, tried a few modifications of attention layer in
order to improve performance, presented and discussed results.
