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

Gabriel Reines March; Craig Dick; Stephen Harrow; Xiangyang Ju; Stephen Marshall

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

Gabriel Reines March, Craig Dick, Stephen Harrow, Xiangyang Ju, Stephen Marshall

Research output: Contribution to conference › Poster › peer-review

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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.

Original language	English
Number of pages	1
Publication status	Published - 25 Jul 2018
Event	40th International Conference of the IEEE Engineering in Medicine and Biology Society - Honolulu, Hawaii, United States Duration: 17 Jul 2018 → 21 Jul 2018 https://embc.embs.org/2018/

Conference

Conference	40th International Conference of the IEEE Engineering in Medicine and Biology Society
Abbreviated title	EMBC 2018
Country/Territory	United States
City	Honolulu, Hawaii
Period	17/07/18 → 21/07/18
Internet address	https://embc.embs.org/2018/

Keywords

deformable image registration
multimodal image fusion
CT imaging

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Reines-March-etal-EMBS2018-Lung-tumor-3D-reconstruction-from-planar-CT-scansAccepted author manuscript, 1.4 MBLicence: CC BY-NC-ND 4.0

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

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.",

keywords = "deformable image registration, multimodal image fusion, CT imaging",

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Lung tumor 3D reconstruction from planar CT scans and registration to micro and macroscopic pathology imaging. / Reines March, Gabriel; Dick, Craig; Harrow, Stephen; Ju, Xiangyang; Marshall, Stephen.

2018. Poster session presented at 40th International Conference of the IEEE Engineering in Medicine and Biology Society, Honolulu, Hawaii, United States.

Research output: Contribution to conference › Poster › peer-review

TY - CONF

T1 - Lung tumor 3D reconstruction from planar CT scans and registration to micro and macroscopic pathology imaging

AU - Reines March, Gabriel

AU - Dick, Craig

AU - Harrow, Stephen

AU - Ju, Xiangyang

AU - Marshall, Stephen

PY - 2018/7/25

Y1 - 2018/7/25

N2 - 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.

AB - 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.

KW - deformable image registration

KW - multimodal image fusion

KW - CT imaging

M3 - Poster

T2 - 40th International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 17 July 2018 through 21 July 2018

ER -

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

Abstract

Conference

Keywords

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