Welcome to the Amira-Avizo Software Use Case Gallery

Below you will find a collection of use cases of our 3D data visualization and analysis software. These use cases include scientific publications, articles, papers, posters, presentations or even videos that show how Amira-Avizo Software is used to address various scientific and industrial research topics.

Use the Domain selector to filter by main application area, and use the Search box to enter keywords related to specific topics you are interested in.

Could tumour volume and major and minor axis based on CTA statistical anatomy improve the pre-operative T-stage in oesophageal cancer?

Could tumour volume and major and minor axis based on CTA statistical anatomy improve the pre-operative T-stage in oesophageal cancer?

Objectives

To statistically study the 3D shape of oesophageal cancer (EC) and its spatial relationships based on computed tomography angiography (CTA) 3D reconstruction, to determine its relationship with T-stages, and to create an optimal T-stage diagnosis protocol based on CTA calculation.

Read more

Runyuan Wang, Xiaoqin Zhang, Wei Wu, Jinfeng Ma, Jincheng Chen, Zhu Zhang, Liqun Liu, Shanshan Xu, Ximei Cao, Yi Wu, Huilin Cui

Read full paper
A new straightforward method for semi-automated segmentation of trabecular bone from cortical bone in diverse and challenging morphologies

A new straightforward method for semi-automated segmentation of trabecular bone from cortical bone in diverse and challenging morphologies

Many physiological, biomechanical, evolutionary and clinical studies that explore skeletal structure and function require successful separation of trabecular from cortical compartments of a bone that has been imaged by X-ray micro-computed tomography (micro-CT) prior to analysis. Separation often involves manual subdivision of these two similarly radio-opaque compartments, which can be time-consuming and subjective. We have developed an objective, semi-automated protocol which reduces user bi... Read more

Eva C. Herbst, Alessandro A. Felder, Lucinda A. E. Evans, Sara Ajami, Behzad Javaheri and Andrew A. Pitsillides

Read full paper
Segmentation of cortical bone, trabecular bone, and medullary pores from micro-CT images using 2D and 3D deep learning models

Segmentation of cortical bone, trabecular bone, and medullary pores from micro-CT images using 2D and 3D deep learning models

Computed tomography (CT) enables rapid imaging of large-scale studies of bone, but those datasets typically require manual segmentation, which is time-consuming and prone to error. Convolutional neural networks (CNNs) offer an automated solution, achieving superior performance on image data. In this methodology-focused paper, we used CNNs to train segmentation models from scratch on 2D and 3D patches from micro-CT scans of otter long bones. These new models, collectively called BONe (Bone One... Read more

Andrew H. Lee, Julian M. Moore, Brandon Vera Covarrubias, Leigha M. Lynch

Read paper