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Items: 11

1.

Deep Learning for Quantification of Epicardial and Thoracic Adipose Tissue from Non-Contrast CT.

Commandeur F, Goeller M, Betancur J, Cadet S, Doris M, Chen X, Berman DS, Slomka PJ, Tamarappoo BK, Dey D.

IEEE Trans Med Imaging. 2018 Feb 9. doi: 10.1109/TMI.2018.2804799. [Epub ahead of print]

PMID:
29994362
2.

Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter Study.

Betancur J, Commandeur F, Motlagh M, Sharir T, Einstein AJ, Bokhari S, Fish MB, Ruddy TD, Kaufmann P, Sinusas AJ, Miller EJ, Bateman TM, Dorbala S, Di Carli M, Germano G, Otaki Y, Tamarappoo BK, Dey D, Berman DS, Slomka PJ.

JACC Cardiovasc Imaging. 2018 Mar 12. pii: S1936-878X(18)30131-1. doi: 10.1016/j.jcmg.2018.01.020. [Epub ahead of print]

PMID:
29550305
3.

Radiomics to Identify High-Risk Atherosclerotic Plaque From Computed Tomography: The Power of Quantification.

Dey D, Commandeur F.

Circ Cardiovasc Imaging. 2017 Dec;10(12). pii: e007254. doi: 10.1161/CIRCIMAGING.117.007254. No abstract available.

PMID:
29233837
4.

Epicardial adipose tissue density and volume are related to subclinical atherosclerosis, inflammation and major adverse cardiac events in asymptomatic subjects.

Goeller M, Achenbach S, Marwan M, Doris MK, Cadet S, Commandeur F, Chen X, Slomka PJ, Gransar H, Cao JJ, Wong ND, Albrecht MH, Rozanski A, Tamarappoo BK, Berman DS, Dey D.

J Cardiovasc Comput Tomogr. 2018 Jan - Feb;12(1):67-73. doi: 10.1016/j.jcct.2017.11.007. Epub 2017 Nov 24.

PMID:
29233634
5.

Population model of bladder motion and deformation based on dominant eigenmodes and mixed-effects models in prostate cancer radiotherapy.

Rios R, De Crevoisier R, Ospina JD, Commandeur F, Lafond C, Simon A, Haigron P, Espinosa J, Acosta O.

Med Image Anal. 2017 May;38:133-149. doi: 10.1016/j.media.2017.03.001. Epub 2017 Mar 8.

6.

Slice correspondence estimation using SURF descriptors and context-based search for prostate whole-mount histology MRI registration.

Guzman L, Commandeur F, Acosta O, Simon A, Fautrel A, Rioux-Leclercq N, Romero E, Mathieu R, de Crevoisier R.

Conf Proc IEEE Eng Med Biol Soc. 2016 Aug;2016:1163-1166. doi: 10.1109/EMBC.2016.7590911.

PMID:
28268532
7.

Haralick textural features on T2 -weighted MRI are associated with biochemical recurrence following radiotherapy for peripheral zone prostate cancer.

Gnep K, Fargeas A, Gutiérrez-Carvajal RE, Commandeur F, Mathieu R, Ospina JD, Rolland Y, Rohou T, Vincendeau S, Hatt M, Acosta O, de Crevoisier R.

J Magn Reson Imaging. 2017 Jan;45(1):103-117. doi: 10.1002/jmri.25335. Epub 2016 Jun 27.

PMID:
27345946
8.

MRI to CT Prostate Registration for Improved Targeting in Cancer External Beam Radiotherapy.

Commandeur F, Simon A, Mathieu R, Nassef M, Arango JDO, Rolland Y, Haigron P, de Crevoisier R, Acosta O.

IEEE J Biomed Health Inform. 2017 Jul;21(4):1015-1026. doi: 10.1109/JBHI.2016.2581881. Epub 2016 Jun 16.

PMID:
27333613
9.

Prostate whole-mount histology reconstruction and registration to MRI for correlating in-vivo observations with biological findings.

Commandeur F, Acosta O, Simon A, Mathieu R, Fautrel A, Gnep K, Haigron P, de Crevoisier R.

Conf Proc IEEE Eng Med Biol Soc. 2015;2015:2399-402. doi: 10.1109/EMBC.2015.7318877.

PMID:
26736777
10.

A tensor-based population value decomposition to explain rectal toxicity after prostate cancer radiotherapy.

Ospina JD, Commandeur F, Ríos R, Dréan G, Correa JC, Simon A, Haigron P, de Crevoisier R, Acosta O.

Med Image Comput Comput Assist Interv. 2013;16(Pt 2):387-94.

11.

[Choice of optimal margins in prostate conformal radiotherapy].

Khalifa J, Commandeur F, Bachaud JM, de Crevoisier R.

Cancer Radiother. 2013 Oct;17(5-6):461-9. doi: 10.1016/j.canrad.2013.06.031. Epub 2013 Aug 20. Review. French.

PMID:
23973458

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