Lung tumor 3D reconstruction from planar CT scans and registration to micro and macroscopic pathology imaging

Tools

Reines March, Gabriel and Dick, Craig and Harrow, Stephen and Ju, Xiangyang and Marshall, Stephen (2018) Lung tumor 3D reconstruction from planar CT scans and registration to micro and macroscopic pathology imaging. In: 40th International Conference of the IEEE Engineering in Medicine and Biology Society, 2018-07-17 - 2018-07-21.

[thumbnail of Reines-March-etal-EMBS2018-Lung-tumor-3D-reconstruction-from-planar-CT-scans]
Preview
 Text. Filename: Reines_March_etal_EMBS2018_Lung_tumor_3D_reconstruction_from_planar_CT_scans.pdf
Accepted Author Manuscript
License: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 logo
Download (1MB)| Preview

Abstract

The overall goal of this project is to ascertain whether a given PET radiotracer reliably and accurately identifies an active cancerous region within the gross tumour volume. The only means to assess it is to compare the PET signal with the gold standard of histopathology. To allow for this comparison both images need to be spatially aligned or registered. However, lung tissue undergoes several deformations following surgical resection and pathological processing. Therefore, these distortions need to be taken into account in order to obtain a truthful mapping. Moreover, PET signals are intrinsically 3D, whereas histopathology slices are planar images. In order to overcome this problem, 2D slices have to be stacked together to reconstruct the original volume prior to registration.

ORCID iDs

Reines March, Gabriel ORCID logoORCID: https://orcid.org/0000-0003-0761-0592, Dick, Craig, Harrow, Stephen, Ju, Xiangyang and Marshall, Stephen ORCID logoORCID: https://orcid.org/0000-0001-7079-5628;
CORE (COnnecting REpositories)