Abstract
In this study, similarity rates of the liver images are determined using 3D geometric transformation methods and numerical comparisons are made. Three geometric transformation methods scaling, rotating, and translating are consecutively applied to 10 intact liver images which are drawn by the radiologists. Atlases of liver images are generated, Dice coefficients are calculated according to the specified atlases and are assessed for various cases. This study is presented as a step to prepare atlas database for segmentation of the injured liver.
Keywords
Dice
Similarity (geometry)
Segmentation
Transformation (genetics)
Atlas (anatomy)
Artificial intelligence
Scaling
Computer science
Geometric transformation
Computer vision
Sørensen–Dice coefficient
Pattern recognition (psychology)
Image (mathematics)
Matrix similarity
Image segmentation
Mathematics
Geometry
Medicine
Anatomy
Mathematical analysis
Subject Areas
Medical Image Segmentation Techniques
·Computer Vision and Pattern Recognition ·Physical Sciences
Medical Imaging and Analysis
·Biomedical Engineering ·Physical Sciences
AI in cancer detection
·Artificial Intelligence ·Physical Sciences