Klyuzhin IS - Search Results

1

Multi-tracer PET correlation analysis reveals disease-specific patterns in Parkinson's disease and asymptomatic LRRK2 pathogenic variant carriers compared to healthy controls.

Mannheim JG, Fu JF, Wegener T, Klyuzhin IS, Vafai N, Shahinfard E, McKenzie J, Strongosky A, Wszolek ZK, Jon Stoessl A, Sossi V. Mannheim JG, et al. Among authors: klyuzhin is. Neuroimage Clin. 2024;42:103600. doi: 10.1016/j.nicl.2024.103600. Epub 2024 Apr 1. Neuroimage Clin. 2024. PMID: 38599001 Free PMC article.

2

Exploring the use of shape and texture descriptors of positron emission tomography tracer distribution in imaging studies of neurodegenerative disease.

Klyuzhin IS, Gonzalez M, Shahinfard E, Vafai N, Sossi V. Klyuzhin IS, et al. J Cereb Blood Flow Metab. 2016 Jun;36(6):1122-34. doi: 10.1177/0271678X15606718. Epub 2015 Oct 6. J Cereb Blood Flow Metab. 2016. PMID: 26661171 Free PMC article.

3

Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments.

Rahmim A, Salimpour Y, Jain S, Blinder SA, Klyuzhin IS, Smith GS, Mari Z, Sossi V. Rahmim A, et al. Among authors: klyuzhin is. Neuroimage Clin. 2016 Feb 23;12:e1-e9. doi: 10.1016/j.nicl.2016.02.012. eCollection 2016. Neuroimage Clin. 2016. PMID: 27995072 Free PMC article.

4

PET Image Reconstruction and Deformable Motion Correction Using Unorganized Point Clouds.

Klyuzhin IS, Sossi V. Klyuzhin IS, et al. IEEE Trans Med Imaging. 2017 Jun;36(6):1263-1275. doi: 10.1109/TMI.2017.2675989. Epub 2017 Mar 2. IEEE Trans Med Imaging. 2017. PMID: 28287962

5

Investigation of serotonergic Parkinson's disease-related covariance pattern using [¹¹C]-DASB/PET.

Fu JF, Klyuzhin I, Liu S, Shahinfard E, Vafai N, McKenzie J, Neilson N, Mabrouk R, Sacheli MA, Wile D, McKeown MJ, Stoessl AJ, Sossi V. Fu JF, et al. Neuroimage Clin. 2018 May 21;19:652-660. doi: 10.1016/j.nicl.2018.05.022. eCollection 2018. Neuroimage Clin. 2018. PMID: 29946508 Free PMC article.

6

Data-driven, voxel-based analysis of brain PET images: Application of PCA and LASSO methods to visualize and quantify patterns of neurodegeneration.

Klyuzhin IS, Fu JF, Hong A, Sacheli M, Shenkov N, Matarazzo M, Rahmim A, Stoessl AJ, Sossi V. Klyuzhin IS, et al. PLoS One. 2018 Nov 5;13(11):e0206607. doi: 10.1371/journal.pone.0206607. eCollection 2018. PLoS One. 2018. PMID: 30395576 Free PMC article.

7

Artificial Neural Network-Based Prediction of Outcome in Parkinson's Disease Patients Using DaTscan SPECT Imaging Features.

Tang J, Yang B, Adams MP, Shenkov NN, Klyuzhin IS, Fotouhi S, Davoodi-Bojd E, Lu L, Soltanian-Zadeh H, Sossi V, Rahmim A. Tang J, et al. Among authors: klyuzhin is. Mol Imaging Biol. 2019 Dec;21(6):1165-1173. doi: 10.1007/s11307-019-01334-5. Mol Imaging Biol. 2019. PMID: 30847821

8

Joint pattern analysis applied to PET DAT and VMAT2 imaging reveals new insights into Parkinson's disease induced presynaptic alterations.

Fu JF, Klyuzhin I, McKenzie J, Neilson N, Shahinfard E, Dinelle K, McKeown MJ, Stoessl AJ, Sossi V. Fu JF, et al. Neuroimage Clin. 2019;23:101856. doi: 10.1016/j.nicl.2019.101856. Epub 2019 May 8. Neuroimage Clin. 2019. PMID: 31091502 Free PMC article.

9

Use of a Tracer-Specific Deep Artificial Neural Net to Denoise Dynamic PET Images.

Klyuzhin IS, Cheng JC, Bevington C, Sossi V. Klyuzhin IS, et al. IEEE Trans Med Imaging. 2020 Feb;39(2):366-376. doi: 10.1109/TMI.2019.2927199. Epub 2019 Jul 5. IEEE Trans Med Imaging. 2020. PMID: 31283475

10

Optimized machine learning methods for prediction of cognitive outcome in Parkinson's disease.

Salmanpour MR, Shamsaei M, Saberi A, Setayeshi S, Klyuzhin IS, Sossi V, Rahmim A. Salmanpour MR, et al. Among authors: klyuzhin is. Comput Biol Med. 2019 Aug;111:103347. doi: 10.1016/j.compbiomed.2019.103347. Epub 2019 Jun 28. Comput Biol Med. 2019. PMID: 31284154

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