Korfiatis P - Search Results

1

Two-stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra-reader and inter-reader reliability at full and reduced radiation dose on an external dataset.

Panda A, Korfiatis P, Suman G, Garg SK, Polley EC, Singh DP, Chari ST, Goenka AH. Panda A, et al. Among authors: korfiatis p. Med Phys. 2021 May;48(5):2468-2481. doi: 10.1002/mp.14782. Epub 2021 Mar 16. Med Phys. 2021. PMID: 33595105

2

MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas.

Korfiatis P, Kline TL, Coufalova L, Lachance DH, Parney IF, Carter RE, Buckner JC, Erickson BJ. Korfiatis P, et al. Med Phys. 2016 Jun;43(6):2835-2844. doi: 10.1118/1.4948668. Med Phys. 2016. PMID: 27277032 Free PMC article.

3

Semiautomated Segmentation of Polycystic Kidneys in T2-Weighted MR Images.

Kline TL, Edwards ME, Korfiatis P, Akkus Z, Torres VE, Erickson BJ. Kline TL, et al. Among authors: korfiatis p. AJR Am J Roentgenol. 2016 Sep;207(3):605-13. doi: 10.2214/AJR.15.15875. Epub 2016 Jun 24. AJR Am J Roentgenol. 2016. PMID: 27341140 Free PMC article.

4

A quantitative symmetry-based analysis of hyperacute ischemic stroke lesions in noncontrast computed tomography.

Peter R, Korfiatis P, Blezek D, Oscar Beitia A, Stepan-Buksakowska I, Horinek D, Flemming KD, Erickson BJ. Peter R, et al. Among authors: korfiatis p. Med Phys. 2017 Jan;44(1):192-199. doi: 10.1002/mp.12015. Epub 2017 Jan 8. Med Phys. 2017. PMID: 28066898 Free PMC article.

5

Toolkits and Libraries for Deep Learning.

Erickson BJ, Korfiatis P, Akkus Z, Kline T, Philbrick K. Erickson BJ, et al. Among authors: korfiatis p. J Digit Imaging. 2017 Aug;30(4):400-405. doi: 10.1007/s10278-017-9965-6. J Digit Imaging. 2017. PMID: 28315069 Free PMC article. Review.

6

Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys.

Kline TL, Korfiatis P, Edwards ME, Blais JD, Czerwiec FS, Harris PC, King BF, Torres VE, Erickson BJ. Kline TL, et al. Among authors: korfiatis p. J Digit Imaging. 2017 Aug;30(4):442-448. doi: 10.1007/s10278-017-9978-1. J Digit Imaging. 2017. PMID: 28550374 Free PMC article.

7

What Does Deep Learning See? Insights From a Classifier Trained to Predict Contrast Enhancement Phase From CT Images.

Philbrick KA, Yoshida K, Inoue D, Akkus Z, Kline TL, Weston AD, Korfiatis P, Takahashi N, Erickson BJ. Philbrick KA, et al. Among authors: korfiatis p. AJR Am J Roentgenol. 2018 Dec;211(6):1184-1193. doi: 10.2214/AJR.18.20331. Epub 2018 Nov 7. AJR Am J Roentgenol. 2018. PMID: 30403527

8

Automated Abdominal Segmentation of CT Scans for Body Composition Analysis Using Deep Learning.

Weston AD, Korfiatis P, Kline TL, Philbrick KA, Kostandy P, Sakinis T, Sugimoto M, Takahashi N, Erickson BJ. Weston AD, et al. Among authors: korfiatis p. Radiology. 2019 Mar;290(3):669-679. doi: 10.1148/radiol.2018181432. Epub 2018 Dec 11. Radiology. 2019. PMID: 30526356

9

RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning.

Philbrick KA, Weston AD, Akkus Z, Kline TL, Korfiatis P, Sakinis T, Kostandy P, Boonrod A, Zeinoddini A, Takahashi N, Erickson BJ. Philbrick KA, et al. Among authors: korfiatis p. J Digit Imaging. 2019 Aug;32(4):571-581. doi: 10.1007/s10278-019-00232-0. J Digit Imaging. 2019. PMID: 31089974 Free PMC article. Review.

10

Complete abdomen and pelvis segmentation using U-net variant architecture.

Weston AD, Korfiatis P, Philbrick KA, Conte GM, Kostandy P, Sakinis T, Zeinoddini A, Boonrod A, Moynagh M, Takahashi N, Erickson BJ. Weston AD, et al. Among authors: korfiatis p. Med Phys. 2020 Nov;47(11):5609-5618. doi: 10.1002/mp.14422. Epub 2020 Oct 7. Med Phys. 2020. PMID: 32740931

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