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Items: 21

1.

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.

Wu N, Phang J, Park J, Shen Y, Huang Z, Zorin M, Jastrzebski S, Fevry T, Katsnelson J, Kim E, Wolfson S, Parikh U, Gaddam S, Lin LLY, Ho K, Weinstein JD, Reig B, Gao Y, Pysarenko HTK, Lewin A, Lee J, Airola K, Mema E, Chung S, Hwang E, Samreen N, Kim SG, Heacock L, Moy L, Cho K, Geras KJ.

IEEE Trans Med Imaging. 2019 Oct 7. doi: 10.1109/TMI.2019.2945514. [Epub ahead of print]

PMID:
31603772
2.

Preliminary study: Breast cancers can be well seen on 3T breast MRI with a half-dose of gadobutrol.

Melsaether AN, Kim E, Mema E, Babb J, Kim SG.

Clin Imaging. 2019 Nov - Dec;58:84-89. doi: 10.1016/j.clinimag.2019.06.014. Epub 2019 Jun 27.

PMID:
31279989
3.

Breast MRI screening for average-risk women: A monte carlo simulation cost-benefit analysis.

Mango VL, Goel A, Mema E, Kwak E, Ha R.

J Magn Reson Imaging. 2019 Jun;49(7):e216-e221. doi: 10.1002/jmri.26334. Epub 2019 Jan 11.

PMID:
30632645
4.

Preliminary analysis: Background parenchymal 18F-FDG uptake in breast cancer patients appears to correlate with background parenchymal enhancement and to vary by distance from the index cancer.

Kim E, Mema E, Axelrod D, Sigmund E, Kim SG, Babb J, Melsaether AN.

Eur J Radiol. 2019 Jan;110:163-168. doi: 10.1016/j.ejrad.2018.11.031. Epub 2018 Nov 28.

PMID:
30599855
5.

Fully Automated Convolutional Neural Network Method for Quantification of Breast MRI Fibroglandular Tissue and Background Parenchymal Enhancement.

Ha R, Chang P, Mema E, Mutasa S, Karcich J, Wynn RT, Liu MZ, Jambawalikar S.

J Digit Imaging. 2019 Feb;32(1):141-147. doi: 10.1007/s10278-018-0114-7.

PMID:
30076489
6.

Evaluation of association between degree of background parenchymal enhancement on MRI and breast cancer subtype.

Ha R, Mango V, Al-Khalili R, Mema E, Friedlander L, Desperito E, Wynn RT.

Clin Imaging. 2018 Sep - Oct;51:307-310. doi: 10.1016/j.clinimag.2018.05.008. Epub 2018 May 5.

PMID:
29945057
7.

Proportion and Clinical Relevance of Intraspinal Air in Patients With Pneumomediastinum.

Behr G, Mema E, Costa K, Garg A.

AJR Am J Roentgenol. 2018 Aug;211(2):321-326. doi: 10.2214/AJR.17.19256. Epub 2018 May 29.

PMID:
29812979
8.

Director gliding in a nematic liquid crystal layer: Quantitative comparison with experiments.

Mema E, Kondic L, Cummings LJ.

Phys Rev E. 2018 Mar;97(3-1):032704. doi: 10.1103/PhysRevE.97.032704.

PMID:
29776080
9.

In the Setting of Negative Mammogram, Is Additional Breast Ultrasound Necessary for Evaluation of Breast Pain?

Mema E, Cho E, Ryu YK, Jadeja P, Wynn R, Taback B, Ha R.

Curr Probl Diagn Radiol. 2019 Mar - Apr;48(2):117-120. doi: 10.1067/j.cpradiol.2017.12.007. Epub 2018 Jan 9.

PMID:
29402490
10.

Does breast MRI background parenchymal enhancement indicate metabolic activity? Qualitative and 3D quantitative computer imaging analysis.

Mema E, Mango VL, Guo X, Karcich J, Yeh R, Wynn RT, Zhao B, Ha RS.

J Magn Reson Imaging. 2018 Mar;47(3):753-759. doi: 10.1002/jmri.25798. Epub 2017 Jun 24.

PMID:
28646614
11.

Effects of flexoelectricity and weak anchoring on a Freedericksz transition cell.

Mema E, Kondic L, Cummings LJ.

Phys Rev E. 2017 Jan;95(1-1):012701. doi: 10.1103/PhysRevE.95.012701. Epub 2017 Jan 5.

PMID:
28208326
12.

Cystic metastatic lymph nodes in malignant melanoma: a case report.

Mema E, Cho E, Ha R, Taback B.

Clin Imaging. 2017 Mar - Apr;42:158-160. doi: 10.1016/j.clinimag.2016.12.006. Epub 2016 Dec 15.

PMID:
28012358
13.

Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging.

Sala E, Mema E, Himoto Y, Veeraraghavan H, Brenton JD, Snyder A, Weigelt B, Vargas HA.

Clin Radiol. 2017 Jan;72(1):3-10. doi: 10.1016/j.crad.2016.09.013. Epub 2016 Oct 11. Review.

14.

Quantitative 3D breast magnetic resonance imaging fibroglandular tissue analysis and correlation with qualitative assessments: a feasibility study.

Ha R, Mema E, Guo X, Mango V, Desperito E, Ha J, Wynn R, Zhao B.

Quant Imaging Med Surg. 2016 Apr;6(2):144-50. doi: 10.21037/qims.2016.03.03.

15.

RAD-AID Asha Jyoti Mammogram Quality Assessment in India: Optimizing Mobile Radiology.

Mango VL, Ha R, Nguyen B, Mema E, Kobeski J, Singh T, Khandelwal N.

J Am Coll Radiol. 2016 Jul;13(7):831-4. doi: 10.1016/j.jacr.2016.03.018. Epub 2016 May 6. No abstract available.

PMID:
27162043
16.

Three-Dimensional Quantitative Validation of Breast Magnetic Resonance Imaging Background Parenchymal Enhancement Assessments.

Ha R, Mema E, Guo X, Mango V, Desperito E, Ha J, Wynn R, Zhao B.

Curr Probl Diagn Radiol. 2016 Sep-Oct;45(5):297-303. doi: 10.1067/j.cpradiol.2016.02.003. Epub 2016 Feb 8.

PMID:
27039221
17.

Substrate-induced gliding in a nematic liquid crystal layer.

Mema E, Kondic L, Cummings LJ.

Phys Rev E Stat Nonlin Soft Matter Phys. 2015 Dec;92(6):062513. doi: 10.1103/PhysRevE.92.062513. Epub 2015 Dec 28.

PMID:
26764717
18.

Electric-field variations within a nematic-liquid-crystal layer.

Cummings LJ, Mema E, Cai C, Kondic L.

Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Jul;90(1):012503. Epub 2014 Jul 3.

PMID:
25122320
19.

A model for Chagas disease with oral and congenital transmission.

Coffield DJ Jr, Spagnuolo AM, Shillor M, Mema E, Pell B, Pruzinsky A, Zetye A.

PLoS One. 2013 Jun 28;8(6):e67267. doi: 10.1371/journal.pone.0067267. Print 2013.

20.

Absence of the glucagon-like peptide-1 receptor does not affect the metabolic phenotype of mice with liver-specific G(s)α deficiency.

Chen M, Mema E, Kelleher J, Nemechek N, Berger A, Wang J, Xie T, Gavrilova O, Drucker DJ, Weinstein LS.

Endocrinology. 2011 Sep;152(9):3343-50. doi: 10.1210/en.2011-0012. Epub 2011 Jul 19.

21.

Effects of deficiency of the G protein Gsα on energy and glucose homeostasis.

Chen M, Nemechek NM, Mema E, Wang J, Weinstein LS.

Eur J Pharmacol. 2011 Jun 11;660(1):119-24. doi: 10.1016/j.ejphar.2010.10.105. Epub 2011 Jan 3. Review.

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