Deep-JASC: joint attenuation and scatter correction in whole-body 18F-FDG PET using a deep residual network

Using domain knowledge for robust and generalizable deep learning-based CT-free PET attenuation and scatter correction.

Guo, Rui
Xue, Song
Hu, Jiaxi
Sari, Hasan
Zeimpekis, Konstantinos
Prenosil, George
Wang, Yue
Zhang, Yu
Viscione, Marco
Sznitman, Raphael
Rominger, Axel
Li, Biao
Shi, Kuangyu
Mingels, Clemens

October 2022

Despite the potential of deep learning (DL)-based methods in substituting CT-based PET attenuation a...

Attenuation correction for brain PET imaging using deep neural network based on Dixon and ZTE MR images

Gong, Kuang
Yang, Jaewon
Kim, Kyungsang
Fakhri, Georges El
Seo, Youngho
Li, Quanzheng

June 2018

Positron emission tomography (PET) is a functional imaging modality widely used in neuroscience stud...

Deep learning based scatter and attenuation estimation in PET imaging

Laurent, Baptiste

May 2022

Afin d’obtenir des images TEP quantitatives, essentielles au diagnostic et au suivi thérapeutique en...

Deep-JASC: joint attenuation and scatter correction in whole-body F-18-FDG PET using a deep residual network

Shiri, Isaac
Arabi, Hossein
Geramifar, Parham
Hajianfar, Ghasem
Ghafarian, Pardis
Rahmim, Arman
Ay, Mohammad Reza
Zaidi, Habib

October 2020

Objective We demonstrate the feasibility of direct generation of attenuation and scatter-corrected i...

Deep-JASC:joint attenuation and scatter correction in whole-body F-18-FDG PET using a deep residual network

Shiri, Isaac
Arabi, Hossein
Geramifar, Parham
Hajianfar, Ghasem
Ghafarian, Pardis
Rahmim, Arman
Ay, Mohammad Reza
Zaidi, Habib

October 2020

Objective We demonstrate the feasibility of direct generation of attenuation and scatter-corrected i...

Deep-JASC: joint attenuation and scatter correction in whole-body 18F-FDG PET using a deep residual network

Shiri, I.
Arabi, H.
Geramifar, P.
Hajianfar, G.
Ghafarian, P.
Rahmim, A.
Ay, M.R.
Zaidi, H.

January 2020

Objective: We demonstrate the feasibility of direct generation of attenuation and scatter-corrected ...

Joint correction of attenuation and scatter in image space using deep convolutional neural networks for dedicated brain 18F-FDG PET.

Yang, Jaewon
Park, Dookun
Seo, Youngho
Gullberg, Grant

April 2019

Dedicated brain positron emission tomography (PET) devices can provide higher-resolution images with...

CT-less Direct Correction of Attenuation and Scatter in the Image Space Using Deep Learning for Whole-Body FDG PET: Potential Benefits and Pitfalls.

Yang, Jaewon
Sohn, Jae Ho
Behr, Spencer C
Gullberg, Grant T
Seo, Youngho

March 2021

PurposeTo demonstrate the feasibility of CT-less attenuation and scatter correction (ASC) in the ima...

Feasibility of Deep Learning-Guided Attenuation and Scatter Correction of Whole-Body 68Ga-PSMA PET Studies in the Image Domain

Mostafapour, Samaneh
Gholamiankhah, Faeze
Dadgar, Habibollah
Arabi, Hossein
Zaidi, Habib

January 2021

This study evaluates the feasibility of direct scatter and attenuation correction of whole-body 68Ga...

Deep learning-guided joint attenuation and scatter correction in multitracer neuroimaging studies

Arabi, Hossein
Bortolin, Karin
Ginovart, Nathalie
Garibotto, Valentina
Zaidi, Habib

September 2020

PET attenuation correction (AC) on systems lacking CT/transmission scanning, such as dedicated brain...

Independent attenuation correction of whole body [<sup>18</sup>F]FDG-PET using a deep learning approach with Generative Adversarial Networks

Armanious, Karim
Hepp, Tobias
Küstner, Thomas
Dittmann, Helmut
Nikolaou, Konstantin
La Fougère, Christian
Yang, Bin
Gatidis, Sergios

January 2020

Background: Attenuation correction (AC) of PET data is usually performed using a second imaging for ...

A deep learning approach for 18F-FDG PET attenuation correction

Fang Liu
Hyungseok Jang
Richard Kijowski
Gengyan Zhao
Tyler Bradshaw
Alan B. McMillan

November 2018

Abstract Background To develop and evaluate the feasibility of a data-driven deep learning approach ...

Towards a Whole Body [18F] FDG Positron Emission Tomography Attenuation Correction Map Synthesizing using Deep Neural Networks

Colmeiro, Ramiro Rodriguez
Verrastro, Claudio
Minsky, Daniel
Grosges, Thomas

April 2021

International audienceThe correction of attenuation effects in Positron Emission Tomography (PET) im...

Deep learning for improving PET/CT attenuation correction by elastic registration of anatomical data.

Schaefferkoetter, J.
Shah, V.
Hayden, C.
Prior, J.O.
Zuehlsdorff, S.

July 2023

For PET/CT, the CT transmission data are used to correct the PET emission data for attenuation. Howe...

Decentralized collaborative multi-institutional PET attenuation and scatter correction using federated deep learning

Shiri Lord, Isaac
Vafaei Sadr, Alireza
Akhavanallaf, Azadeh
Salimi, Yazdan
Sanaat, Amirhossein
Amini, Mehdi
Razeghi, Behrooz
Saberi Manesh, Abdollah
Arabi, Hossein
Ferdowsi, Sohrab
Voloshynovskiy, Slava
Gündüz, Deniz
Rahmim, Arman
Zaidi, Habib

January 2023

Purpose: Attenuation correction and scatter compensation (AC/SC) are two main steps toward quantita...

Using domain knowledge for robust and generalizable deep learning-based CT-free PET attenuation and scatter correction.

Guo, Rui
Xue, Song
Hu, Jiaxi
Sari, Hasan
Zeimpekis, Konstantinos
Prenosil, George
Wang, Yue
Zhang, Yu
Viscione, Marco
Sznitman, Raphael
Rominger, Axel
Li, Biao
Shi, Kuangyu
Mingels, Clemens

October 2022

Despite the potential of deep learning (DL)-based methods in substituting CT-based PET attenuation a...

Attenuation correction for brain PET imaging using deep neural network based on Dixon and ZTE MR images

Gong, Kuang
Yang, Jaewon
Kim, Kyungsang
Fakhri, Georges El
Seo, Youngho
Li, Quanzheng

June 2018

Positron emission tomography (PET) is a functional imaging modality widely used in neuroscience stud...

Deep learning based scatter and attenuation estimation in PET imaging

Laurent, Baptiste

May 2022

Afin d’obtenir des images TEP quantitatives, essentielles au diagnostic et au suivi thérapeutique en...

Deep-JASC: joint attenuation and scatter correction in whole-body F-18-FDG PET using a deep residual network

Shiri, Isaac
Arabi, Hossein
Geramifar, Parham
Hajianfar, Ghasem
Ghafarian, Pardis
Rahmim, Arman
Ay, Mohammad Reza
Zaidi, Habib

October 2020

Objective We demonstrate the feasibility of direct generation of attenuation and scatter-corrected i...

Deep-JASC:joint attenuation and scatter correction in whole-body F-18-FDG PET using a deep residual network

Shiri, Isaac
Arabi, Hossein
Geramifar, Parham
Hajianfar, Ghasem
Ghafarian, Pardis
Rahmim, Arman
Ay, Mohammad Reza
Zaidi, Habib

October 2020

Objective We demonstrate the feasibility of direct generation of attenuation and scatter-corrected i...

Deep-JASC: joint attenuation and scatter correction in whole-body 18F-FDG PET using a deep residual network

Shiri, I.
Arabi, H.
Geramifar, P.
Hajianfar, G.
Ghafarian, P.
Rahmim, A.
Ay, M.R.
Zaidi, H.

January 2020

Objective: We demonstrate the feasibility of direct generation of attenuation and scatter-corrected ...

Joint correction of attenuation and scatter in image space using deep convolutional neural networks for dedicated brain 18F-FDG PET.

Yang, Jaewon
Park, Dookun
Seo, Youngho
Gullberg, Grant

April 2019

Dedicated brain positron emission tomography (PET) devices can provide higher-resolution images with...

CT-less Direct Correction of Attenuation and Scatter in the Image Space Using Deep Learning for Whole-Body FDG PET: Potential Benefits and Pitfalls.

Yang, Jaewon
Sohn, Jae Ho
Behr, Spencer C
Gullberg, Grant T
Seo, Youngho

March 2021

PurposeTo demonstrate the feasibility of CT-less attenuation and scatter correction (ASC) in the ima...

Feasibility of Deep Learning-Guided Attenuation and Scatter Correction of Whole-Body 68Ga-PSMA PET Studies in the Image Domain

Mostafapour, Samaneh
Gholamiankhah, Faeze
Dadgar, Habibollah
Arabi, Hossein
Zaidi, Habib

January 2021

This study evaluates the feasibility of direct scatter and attenuation correction of whole-body 68Ga...

Deep learning-guided joint attenuation and scatter correction in multitracer neuroimaging studies

Arabi, Hossein
Bortolin, Karin
Ginovart, Nathalie
Garibotto, Valentina
Zaidi, Habib

September 2020

PET attenuation correction (AC) on systems lacking CT/transmission scanning, such as dedicated brain...

Independent attenuation correction of whole body [<sup>18</sup>F]FDG-PET using a deep learning approach with Generative Adversarial Networks

Armanious, Karim
Hepp, Tobias
Küstner, Thomas
Dittmann, Helmut
Nikolaou, Konstantin
La Fougère, Christian
Yang, Bin
Gatidis, Sergios

January 2020

Background: Attenuation correction (AC) of PET data is usually performed using a second imaging for ...

A deep learning approach for 18F-FDG PET attenuation correction

Fang Liu
Hyungseok Jang
Richard Kijowski
Gengyan Zhao
Tyler Bradshaw
Alan B. McMillan

November 2018

Abstract Background To develop and evaluate the feasibility of a data-driven deep learning approach ...

Towards a Whole Body [18F] FDG Positron Emission Tomography Attenuation Correction Map Synthesizing using Deep Neural Networks

Colmeiro, Ramiro Rodriguez
Verrastro, Claudio
Minsky, Daniel
Grosges, Thomas

April 2021

International audienceThe correction of attenuation effects in Positron Emission Tomography (PET) im...

Deep learning for improving PET/CT attenuation correction by elastic registration of anatomical data.

Schaefferkoetter, J.
Shah, V.
Hayden, C.
Prior, J.O.
Zuehlsdorff, S.

July 2023

For PET/CT, the CT transmission data are used to correct the PET emission data for attenuation. Howe...

Decentralized collaborative multi-institutional PET attenuation and scatter correction using federated deep learning

Shiri Lord, Isaac
Vafaei Sadr, Alireza
Akhavanallaf, Azadeh
Salimi, Yazdan
Sanaat, Amirhossein
Amini, Mehdi
Razeghi, Behrooz
Saberi Manesh, Abdollah
Arabi, Hossein
Ferdowsi, Sohrab
Voloshynovskiy, Slava
Gündüz, Deniz
Rahmim, Arman
Zaidi, Habib

January 2023

Purpose: Attenuation correction and scatter compensation (AC/SC) are two main steps toward quantita...

Using domain knowledge for robust and generalizable deep learning-based CT-free PET attenuation and scatter correction.

Guo, Rui
Xue, Song
Hu, Jiaxi
Sari, Hasan
Zeimpekis, Konstantinos
Prenosil, George
Wang, Yue
Zhang, Yu
Viscione, Marco
Sznitman, Raphael
Rominger, Axel
Li, Biao
Shi, Kuangyu
Mingels, Clemens

October 2022

Despite the potential of deep learning (DL)-based methods in substituting CT-based PET attenuation a...

Attenuation correction for brain PET imaging using deep neural network based on Dixon and ZTE MR images

Gong, Kuang
Yang, Jaewon
Kim, Kyungsang
Fakhri, Georges El
Seo, Youngho
Li, Quanzheng

June 2018

Positron emission tomography (PET) is a functional imaging modality widely used in neuroscience stud...

Deep learning based scatter and attenuation estimation in PET imaging

Laurent, Baptiste

May 2022

Afin d’obtenir des images TEP quantitatives, essentielles au diagnostic et au suivi thérapeutique en...

Deep-JASC: joint attenuation and scatter correction in whole-body 18F-FDG PET using a deep residual network

Abstract

Extracted data

Deep-JASC: joint attenuation and scatter correction in whole-body 18F-FDG PET using a deep residual network

Abstract

Extracted data

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