Format
Sort by
Items per page

Send to

Choose Destination

Links from PubMed

Items: 1 to 20 of 99

1.

Measurement of Glomerular Filtration Rate using Quantitative SPECT/CT and Deep-learning-based Kidney Segmentation.

Park J, Bae S, Seo S, Park S, Bang JI, Han JH, Lee WW, Lee JS.

Sci Rep. 2019 Mar 12;9(1):4223. doi: 10.1038/s41598-019-40710-7.

2.

Automatic renal segmentation for MR urography using 3D-GrabCut and random forests.

Yoruk U, Hargreaves BA, Vasanawala SS.

Magn Reson Med. 2018 Mar;79(3):1696-1707. doi: 10.1002/mrm.26806. Epub 2017 Jun 27.

3.

Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease.

Kim Y, Ge Y, Tao C, Zhu J, Chapman AB, Torres VE, Yu AS, Mrug M, Bennett WM, Flessner MF, Landsittel DP, Bae KT; Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP).

Clin J Am Soc Nephrol. 2016 Apr 7;11(4):576-84. doi: 10.2215/CJN.08300815. Epub 2016 Jan 21.

4.

A computational pipeline for quantification of pulmonary infections in small animal models using serial PET-CT imaging.

Bagci U, Foster B, Miller-Jaster K, Luna B, Dey B, Bishai WR, Jonsson CB, Jain S, Mollura DJ.

EJNMMI Res. 2013 Jul 23;3(1):55. doi: 10.1186/2191-219X-3-55.

5.

Automatic Segmentation of Kidneys using Deep Learning for Total Kidney Volume Quantification in Autosomal Dominant Polycystic Kidney Disease.

Sharma K, Rupprecht C, Caroli A, Aparicio MC, Remuzzi A, Baust M, Navab N.

Sci Rep. 2017 May 17;7(1):2049. doi: 10.1038/s41598-017-01779-0.

6.

Deep Learning Renal Segmentation for Fully Automated Radiation Dose Estimation in Unsealed Source Therapy.

Jackson P, Hardcastle N, Dawe N, Kron T, Hofman MS, Hicks RJ.

Front Oncol. 2018 Jun 14;8:215. doi: 10.3389/fonc.2018.00215. eCollection 2018.

7.

AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.

Zhu W, Huang Y, Zeng L, Chen X, Liu Y, Qian Z, Du N, Fan W, Xie X.

Med Phys. 2019 Feb;46(2):576-589. doi: 10.1002/mp.13300. Epub 2018 Dec 17.

PMID:
30480818
8.

Fully automatic region of interest selection in glomerular filtration rate estimation from 99mTc-DTPA renogram.

Lin KJ, Huang JY, Chen YS.

J Digit Imaging. 2011 Dec;24(6):1010-23. doi: 10.1007/s10278-011-9361-6.

9.

[Multi-slice spiral CT scan with lower dose for preoperative evaluation: living renal donor kidney morphology and the quantification of unilateral glomerular filtration rate].

Su C, Guo Y, Wang CX, Yan CG, Zhou XH, Liu LS, Zhang L.

Zhonghua Yi Xue Za Zhi. 2011 Oct 18;91(38):2697-701. Chinese.

PMID:
22321980
10.

Deep-learning-based detection and segmentation of organs at risk in nasopharyngeal carcinoma computed tomographic images for radiotherapy planning.

Liang S, Tang F, Huang X, Yang K, Zhong T, Hu R, Liu S, Yuan X, Zhang Y.

Eur Radiol. 2019 Apr;29(4):1961-1967. doi: 10.1007/s00330-018-5748-9. Epub 2018 Oct 9.

PMID:
30302589
11.

Deep learning for segmentation of 49 selected bones in CT scans: First step in automated PET/CT-based 3D quantification of skeletal metastases.

Lindgren Belal S, Sadik M, Kaboteh R, Enqvist O, Ulén J, Poulsen MH, Simonsen J, Høilund-Carlsen PF, Edenbrandt L, Trägårdh E.

Eur J Radiol. 2019 Apr;113:89-95. doi: 10.1016/j.ejrad.2019.01.028. Epub 2019 Feb 1.

PMID:
30927965
12.

Automatic lung segmentation in functional SPECT images using active shape models trained on reference lung shapes from CT.

Cheimariotis GA, Al-Mashat M, Haris K, Aletras AH, Jögi J, Bajc M, Maglaveras N, Heiberg E.

Ann Nucl Med. 2018 Feb;32(2):94-104. doi: 10.1007/s12149-017-1223-y. Epub 2017 Dec 13.

13.

Quantitative Single-Photon Emission Computed Tomography/Computed Tomography for Glomerular Filtration Rate Measurement.

Kang YK, Park S, Suh MS, Byun SS, Chae DW, Lee WW.

Nucl Med Mol Imaging. 2017 Dec;51(4):338-346. doi: 10.1007/s13139-017-0491-8. Epub 2017 Aug 24.

14.

A semiautomatic segmentation method for prostate in CT images using local texture classification and statistical shape modeling.

Shahedi M, Halicek M, Guo R, Zhang G, Schuster DM, Fei B.

Med Phys. 2018 Jun;45(6):2527-2541. doi: 10.1002/mp.12898. Epub 2018 Apr 23.

PMID:
29611216
15.

Estimating glomerular filtration rate in kidney donors: a model constructed with renal volume measurements from donor CT scans.

Herts BR, Sharma N, Lieber M, Freire M, Goldfarb DA, Poggio ED.

Radiology. 2009 Jul;252(1):109-16. doi: 10.1148/radiol.2521081873. Epub 2009 May 12.

PMID:
19435940
16.

Automatic multiorgan segmentation in thorax CT images using U-net-GAN.

Dong X, Lei Y, Wang T, Thomas M, Tang L, Curran WJ, Liu T, Yang X.

Med Phys. 2019 Feb 27. doi: 10.1002/mp.13458. [Epub ahead of print]

PMID:
30810231
17.

A combined learning algorithm for prostate segmentation on 3D CT images.

Ma L, Guo R, Zhang G, Schuster DM, Fei B.

Med Phys. 2017 Nov;44(11):5768-5781. doi: 10.1002/mp.12528. Epub 2017 Sep 22.

18.

Automatic segmentation of the prostate on CT images using deep learning and multi-atlas fusion.

Ma L, Guo R, Zhang G, Tade F, Schuster DM, Nieh P, Master V, Fei B.

Proc SPIE Int Soc Opt Eng. 2017 Feb;10133. pii: 101332O. doi: 10.1117/12.2255755. Epub 2017 Feb 24.

19.

Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.

Hu P, Wu F, Peng J, Bao Y, Chen F, Kong D.

Int J Comput Assist Radiol Surg. 2017 Mar;12(3):399-411. doi: 10.1007/s11548-016-1501-5. Epub 2016 Nov 24.

PMID:
27885540
20.

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.

J Digit Imaging. 2017 Aug;30(4):442-448. doi: 10.1007/s10278-017-9978-1.

Supplemental Content

Support Center