Automated methods for volume segmentation/analysis, e.g., machine learning
International Conference on Tomography of Materials & Structures
Days
Monday, 22nd July
Tuesday, 23rd July
Wednesday, 24th July
Thursday, 25th July
Friday, 26th July
Tracks
Advances in tomography using alternative/novel contrast modes
Hardware and acquisition techniques for tomography
Advances in tomographic image reconstruction
Digital Volume Correlation
Automated methods for volume segmentation/analysis, e.g., machine learning
Advanced-materials e.g. composites, foams & engineered tissue
Construction materials e.g. timber & concrete
Biological and biomedical structures
Geological structures
Search
Speakers
Theme 2: Automated methods for volume segmentation/analysis, e.g., machine learning
11:00AM - 12:40PM
Thursday, 25th July
Kuranda
Chair: Sergei Evsevleev
Modelling intensity and gradient distribution of 3D tomography data for direct extraction of physical parameters and robust evaluation of segmentation
-
Elise O Brenne
FiberFind: Machine learning-based segmentation and identification of individual fibers in µCT images of fibrous media
-
Andreas Grießer
More than pretty images – Towards confidence bounds on segmentation thresholds
-
Peter Moonen
INSEGT FIBRE: A POWERFUL SEGMENTATION TOOL FOR QUANTIFYING FIBRE ARCHITECTURE IN COMPOSITES
-
Monica J Emerson
Multi-Branch Deep Residual Convolutional Neural Networks for Enhancing the Spatial Resolution of 3D Computed Tomography Images.
-
sven simon