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Smartphone-Based Color Measurement of Tooth Shade Guide in Clinical Lighting Conditions

Radziun Agnieszka, Doniec Rafał, Sieciński Szymon, Piaseczna Natalia, Mocny-Pachońska Katarzyna, Cieślik-Wegemund Marta, Duraj Konrad, Tanasiewicz Marta, Tkacz Ewaryst

Annals of Computer Science and Information Systems

2021

Vol. 25

409--413

Caries is a common disease of hard tissues of teeth which results in dental cavities, which are usually replaced by dental filling. Matching the color of a dental filling is usually a subjective assessment. In this study we conducted a color analysis of GC Gradia Direct shade guide in the lighting conditions of the dental office. Color measurement was performed using Color Grab mobile app and the results were acquired as values of RGB and HSV values. The results indicate the possibility of identifying each shade of tooth by the most prominent changes in RGB, and/or HSV components.

Instance Segmentation Model Created from Three Semantic Segmentations of Mask, Boundary and Centroid Pixels Verified on GlaS Dataset

Malík Peter, Krištofík Štefan, Knapová Kristína

Annals of Computer Science and Information Systems

2020

Vol. 21

569--576

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.