Instance Segmentation Model Created from Three Semantic Segmentations of Mask, Boundary and Centroid Pixels Verified on GlaS Dataset
Peter Malík, Kristína Knapová, Štefan Krištofík · Annals of Computer Science and Information Systems · 2020
Segmentation is the key computer vision task in modern medicine applications.Instance segmentation became the prevalent way to improve segmentation performance in recent years.This work proposes a novel way to design an instance segmentation model that combines 3 semantic segmentation models dedicated for foreground, boundary and centroid predictions.It contains no detector so it is orthogonal to a standard instance segmentation design and can be used to improve the performance of a standard design.The presented custom designed model is verified on the Gland Segmentation in Colon Histology Images dataset.