Search

Your search keyword '"Marsden, Paul K."' showing total 397 results
Start Over Author "Marsden, Paul K."
397 results on '"Marsden, Paul K."'

4. Deep learned triple-tracer multiplexed PET myocardial image separation.

Author

Pan, Bolin, Marsden, Paul K., and Reader, Andrew J.

Subjects
NOISE control, COMPUTER simulation, RESEARCH funding, DEEP learning, ANALYSIS of variance, CONCEPTUAL structures, EMISSION-computed tomography, DIGITAL image processing
Abstract

Introduction: In multiplexed positron emission tomography (mPET) imaging, physiological and pathological information from different radiotracers can be observed simultaneously in a single dynamic PET scan. The separation of mPET signals within a single PET scan is challenging due to the fact that the PET scanner measures the sum of the PET signals of all the tracers. The conventional multitracer compartment modeling (MTCM) method requires staggered injections and assumes that the arterial input functions (AIFs) of each tracer are known. Methods: In this work, we propose a deep learning-based method to separate triple-tracer PET images without explicitly knowing the AIFs. A dynamic tripletracer noisy MLEM reconstruction was used as the network input, and dynamic single-tracer noisy MLEM reconstructions were used as training labels. Results: A simulation study was performed to evaluate the performance of the proposed framework on triple-tracer ([18F]FDG+82Rb+[94mTc]sestamibi) PET myocardial imaging. The results show that the proposed methodology substantially reduced the noise level compared to the results obtained from single-tracer imaging. Additionally, it achieved lower bias and standard deviation in the separated single-tracer images compared to the MTCM-based method at both the voxel and region of interest (ROI) levels. Discussion: As compared to MTCM separation, the proposed method uses spatiotemporal information for separation, which improves the separation performance at both the voxel and ROI levels. The simulation study also demonstrates the feasibility and potential of the proposed DL-based method for the application to pre-clinical and clinical studies. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

6. Deep Learning Based Approach to Quantification of PET Tracer Uptake in Small Tumors

Author

Dal Toso, Laura, Pfaehler, Elisabeth, Boellaard, Ronald, Schnabel, Julia A., Marsden, Paul K., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Knoll, Florian, editor, Maier, Andreas, editor, Rueckert, Daniel, editor, and Ye, Jong Chul, editor

Published
2019
Full Text
View/download PDF

8. Evaluation of Strategies for PET Motion Correction - Manifold Learning vs. Deep Learning

Author

Clough, James R., Balfour, Daniel R., Prieto, Claudia, Reader, Andrew J., Marsden, Paul K., King, Andrew P., Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Stoyanov, Danail, editor, Taylor, Zeike, editor, Kia, Seyed Mostafa, editor, Oguz, Ipek, editor, Reyes, Mauricio, editor, Martel, Anne, editor, Maier-Hein, Lena, editor, Marquand, Andre F., editor, Duchesnay, Edouard, editor, Löfstedt, Tommy, editor, Landman, Bennett, editor, Cardoso, M. Jorge, editor, Silva, Carlos A., editor, Pereira, Sergio, editor, and Meier, Raphael, editor

Published
2018
Full Text
View/download PDF

11. Efficient Deformable Motion Correction for 3-D Abdominal MRI Using Manifold Regression

Author

Chen, Xin, Balfour, Daniel R., Marsden, Paul K., Reader, Andrew J., Prieto, Claudia, King, Andrew P., Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Descoteaux, Maxime, editor, Maier-Hein, Lena, editor, Franz, Alfred, editor, Jannin, Pierre, editor, Collins, D. Louis, editor, and Duchesne, Simon, editor

Published
2017
Full Text
View/download PDF

14. Dynamic Volume Reconstruction from Multi-slice Abdominal MRI Using Manifold Alignment

Author

Chen, Xin, Usman, Muhammad, Balfour, Daniel R., Marsden, Paul K., Reader, Andrew J., Prieto, Claudia, King, Andrew P., Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Ourselin, Sebastien, editor, Joskowicz, Leo, editor, Sabuncu, Mert R., editor, Unal, Gozde, editor, and Wells, William, editor

Published
2016
Full Text
View/download PDF

22. Validation of PET Imaging by Alignment to Histology Slices

Author

Edwards, Philip J., Nijmeh, Ayman D., McGurk, Mark, Odell, Edward, Fenlon, Michael R., Marsden, Paul K., Hawkes, David J., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Duncan, James S., editor, and Gerig, Guido, editor

Published
2005
Full Text
View/download PDF

34. FDG PET and PET/CT: EANM procedure guidelines for tumour PET imaging: version 1.0

Author

Boellaard, Ronald, O’Doherty, Mike J., Weber, Wolfgang A., Mottaghy, Felix M., Lonsdale, Markus N., Stroobants, Sigrid G., Oyen, Wim J. G., Kotzerke, Joerg, Hoekstra, Otto S., Pruim, Jan, Marsden, Paul K., Tatsch, Klaus, Hoekstra, Corneline J., Visser, Eric P., Arends, Bertjan, Verzijlbergen, Fred J., Zijlstra, Josee M., Comans, Emile F. I., Lammertsma, Adriaan A., Paans, Anne M., Willemsen, Antoon T., Beyer, Thomas, Bockisch, Andreas, Schaefer-Prokop, Cornelia, Delbeke, Dominique, Baum, Richard P., Chiti, Arturo, and Krause, Bernd J.

Published
2010
Full Text
View/download PDF

35. Hemisphere-specific episodic memory networks in the human brain: a correlation study between intracarotid amobarbital test and [[sup.18]F]FDG-PET

Author

Akanuma, Nozomi, Reed, Laurence J., Marsden, Paul K., Jarosz, Jozeph, Adachi, Naoto, Hallett, William A., Alarcon, Gonzalo, Morris, Robin G., and Koutroumanidis, Michael

Subjects
Amobarbital -- Dosage and administration, Amobarbital -- Research, Epileptics -- Medical examination, Episodic memory -- Health aspects, Episodic memory -- Research, PET imaging -- Usage, PET imaging -- Health aspects, Health, Psychology and mental health
Published
2009

37. Additional file 1 of Evaluation of [13N]ammonia positron emission tomography as a potential method for quantifying glutamine synthetase activity in the human brain

Author

Egerton, Alice, Dunn, Joel T., Singh, Nisha, Zilin Yu, O’Doherty, Jim, Koychev, Ivan, Webb, Jessica, Claridge, Simon, Turkheimer, Federico E., Marsden, Paul K., Hammers, Alexander, and Gee, Antony

Subjects
InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, ComputingMilieux_COMPUTERSANDEDUCATION, Data_FILES, ComputerApplications_COMPUTERSINOTHERSYSTEMS
Abstract

Additional file 1. Supplementary Information.

Published
2020
Full Text
View/download PDF

38. The effect of high count rates on cardiac perfusion quantification in a simultaneous PET-MR system using a cardiac perfusion phantom

Author

O’ Doherty, Jim, Chalampalakis, Zacharias, Schleyer, Paul, Nazir, Muhummad Sohaib, Chiribiri, Amedeo, and Marsden, Paul K.

Subjects
Perfusion, lcsh:Medical physics. Medical radiology. Nuclear medicine, Dead time, PET-MR, lcsh:R895-920, Cardiac PET, Original Research
Abstract

Background PET-MRI is under investigation as a new strategy for quantitative myocardial perfusion imaging. Consideration is required as to the maximum scanner count rate in order to limit dead-time losses resulting from administered activity in the scanner field of view during the first pass of the radiotracer. Results We performed a decaying-source experiment to investigate the high count-rate performance of a PET-MR system (Siemens mMR) over the expected range of activities during a clinical study. We also performed imaging of a cardiac perfusion phantom, which provides an experimental simulation of clinical transit of a simultaneous radiotracer (phantom injected activities range 252 to 997 MBq) and gadolinium-based contrast agent (GBCA). Time-activity and time-intensity curves of the aorta and myocardium compartments from PET and MR images were determined, and quantification of perfusion was then performed using a standard cardiac kinetic model. The decaying-source experiment showed a maximum noise equivalent count rate (NECRmax) of 286 kcps at a singles rate of 47.1 Mcps. NECR was maintained within 5% (NECR95%) of the NECRmax with a singles rate of 34.1 Mcps, corresponding to 310 MBq in the phantom. Count-rate performance was degraded above the singles rate of 64.9 Mcps due to the number of detection events impacting the quantitative accuracy of reconstructed images. A 10% bias in image activity concentration was observed between singles rates of 78.2 and 82.9 Mcps. Perfusion phantom experiments showed that image-based activity concentration and quantified values of perfusion were affected by count losses when the total singles rate was greater than 64.9 Mcps. This occurred during the peak arterial input function (AIF) phase of imaging for injected activities to the phantom of 600 MBq and greater. Conclusions Care should be taken to avoid high count-rate losses in simultaneous PET-MRI studies. Based on our results in phantoms, bias in reconstructed images should be avoided by adhering to a singles rate lower than 64.9 Mcps on the mMR system. Quantification of perfusion values using singles rates higher than 64.9 Mcps on this system may be compromised and should be avoided.

Published
2017

Catalog

Books, media, physical & digital resources
See catalog results