Synthetic Positron Emission Tomography Using Conditional-Generative Adversarial Networks for Healthy Bone Marrow Baseline Image Generation

Patrick Leydon; Martin O'Connell; Derek Greene; Kathleen Curran

doi:10.21427/xmkn-d265

Synthetic Positron Emission Tomography Using Conditional-Generative Adversarial Networks for Healthy Bone Marrow Baseline Image Generation

Patrick Leydon, Martin O'Connell, Derek Greene, Kathleen Curran

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

Abstract

A Conditional-Generative Adversarial Network has been used for a supervised image-to-image transla- tion task which outputs a synthetic PET scan based on real patient CT data. The network is trained using only data of patients with healthy bone marrow metabolism. This allows for a patient specific synthetic healthy baseline scan to be produced. This can be used by a clinician for comparison to real PET data in the absence of a baseline scan or to aid in the diagnosis of conditions such as Multiple Myeloma which manifest as changes in bone marrow metabolism.

Original language	English
DOIs	https://doi.org/10.21427/xmkn-d265
Publication status	Published - 1 Jan 2019
Externally published	Yes
Event	IMVIP 2019: Irish Machine Vision & Image Processing - Technological University Dublin, Dublin, Ireland Duration: 28 Aug 2019 → 30 Aug 2019

Conference

Conference	IMVIP 2019: Irish Machine Vision & Image Processing
Country/Territory	Ireland
City	Dublin
Period	28/08/19 → 30/08/19

Keywords

Conditional-Generative Adversarial Network
supervised image-to-image translation
synthetic PET scan
real patient CT data
healthy bone marrow metabolism
baseline scan
diagnosis
Multiple Myeloma
bone marrow metabolism

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10.21427/xmkn-d265Licence: CC BY-NC-SA

Cite this

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title = "Synthetic Positron Emission Tomography Using Conditional-Generative Adversarial Networks for Healthy Bone Marrow Baseline Image Generation",

abstract = "A Conditional-Generative Adversarial Network has been used for a supervised image-to-image transla- tion task which outputs a synthetic PET scan based on real patient CT data. The network is trained using only data of patients with healthy bone marrow metabolism. This allows for a patient specific synthetic healthy baseline scan to be produced. This can be used by a clinician for comparison to real PET data in the absence of a baseline scan or to aid in the diagnosis of conditions such as Multiple Myeloma which manifest as changes in bone marrow metabolism.",

keywords = "Conditional-Generative Adversarial Network, supervised image-to-image translation, synthetic PET scan, real patient CT data, healthy bone marrow metabolism, baseline scan, diagnosis, Multiple Myeloma, bone marrow metabolism",

author = "Patrick Leydon and Martin O'Connell and Derek Greene and Kathleen Curran",

year = "2019",

month = jan,

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doi = "10.21427/xmkn-d265",

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T1 - Synthetic Positron Emission Tomography Using Conditional-Generative Adversarial Networks for Healthy Bone Marrow Baseline Image Generation

AU - Leydon, Patrick

AU - O'Connell, Martin

AU - Greene, Derek

AU - Curran, Kathleen

PY - 2019/1/1

Y1 - 2019/1/1

N2 - A Conditional-Generative Adversarial Network has been used for a supervised image-to-image transla- tion task which outputs a synthetic PET scan based on real patient CT data. The network is trained using only data of patients with healthy bone marrow metabolism. This allows for a patient specific synthetic healthy baseline scan to be produced. This can be used by a clinician for comparison to real PET data in the absence of a baseline scan or to aid in the diagnosis of conditions such as Multiple Myeloma which manifest as changes in bone marrow metabolism.

AB - A Conditional-Generative Adversarial Network has been used for a supervised image-to-image transla- tion task which outputs a synthetic PET scan based on real patient CT data. The network is trained using only data of patients with healthy bone marrow metabolism. This allows for a patient specific synthetic healthy baseline scan to be produced. This can be used by a clinician for comparison to real PET data in the absence of a baseline scan or to aid in the diagnosis of conditions such as Multiple Myeloma which manifest as changes in bone marrow metabolism.

KW - Conditional-Generative Adversarial Network

KW - supervised image-to-image translation

KW - synthetic PET scan

KW - real patient CT data

KW - healthy bone marrow metabolism

KW - baseline scan

KW - diagnosis

KW - Multiple Myeloma

KW - bone marrow metabolism

U2 - 10.21427/xmkn-d265

DO - 10.21427/xmkn-d265

M3 - Paper

T2 - IMVIP 2019: Irish Machine Vision & Image Processing

Y2 - 28 August 2019 through 30 August 2019

ER -

Synthetic Positron Emission Tomography Using Conditional-Generative Adversarial Networks for Healthy Bone Marrow Baseline Image Generation

Abstract

Conference

Keywords

Access to Document

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Cite this