Rahmim A - Search Results

1

PSMA-Hornet: Fully-automated, multi-target segmentation of healthy organs in PSMA PET/CT images.

Klyuzhin IS, Chaussé G, Bloise I, Harsini S, Ferres JL, Uribe C, Rahmim A. Klyuzhin IS, et al. Among authors: rahmim a. Med Phys. 2024 Feb;51(2):1203-1216. doi: 10.1002/mp.16658. Epub 2023 Aug 6. Med Phys. 2024. PMID: 37544015

2

Point/counterpoint. Resolution modeling enhances PET imaging.

Alessio AM, Rahmim A, Orton CG. Alessio AM, et al. Among authors: rahmim a. Med Phys. 2013 Dec;40(12):120601. doi: 10.1118/1.4821088. Med Phys. 2013. PMID: 24320486 No abstract available.

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. 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

Recovery of missing data in partial geometry PET scanners: Compensation in projection space vs image space.

Shojaeilangari S, Schmidtlein CR, Rahmim A, Ay MR. Shojaeilangari S, et al. Among authors: rahmim a. Med Phys. 2018 Dec;45(12):5437-5449. doi: 10.1002/mp.13225. Epub 2018 Oct 25. Med Phys. 2018. PMID: 30288762 Free PMC article.

5

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. Among authors: rahmim a. PLoS One. 2018 Nov 5;13(11):e0206607. doi: 10.1371/journal.pone.0206607. eCollection 2018. PLoS One. 2018. PMID: 30395576 Free PMC article.

6

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: rahmim a. Mol Imaging Biol. 2019 Dec;21(6):1165-1173. doi: 10.1007/s11307-019-01334-5. Mol Imaging Biol. 2019. PMID: 30847821

7

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: rahmim a. Comput Biol Med. 2019 Aug;111:103347. doi: 10.1016/j.compbiomed.2019.103347. Epub 2019 Jun 28. Comput Biol Med. 2019. PMID: 31284154

8

The impact of iterative reconstruction protocol, signal-to-background ratio and background activity on measurement of PET spatial resolution.

Rezaei S, Ghafarian P, Bakhshayesh-Karam M, Uribe CF, Rahmim A, Sarkar S, Ay MR. Rezaei S, et al. Among authors: rahmim a. Jpn J Radiol. 2020 Mar;38(3):231-239. doi: 10.1007/s11604-019-00914-3. Epub 2020 Jan 1. Jpn J Radiol. 2020. PMID: 31894449

9

Machine learning methods for optimal prediction of motor outcome in Parkinson's disease.

Salmanpour MR, Shamsaei M, Saberi A, Klyuzhin IS, Tang J, Sossi V, Rahmim A. Salmanpour MR, et al. Among authors: rahmim a. Phys Med. 2020 Jan;69:233-240. doi: 10.1016/j.ejmp.2019.12.022. Epub 2020 Jan 7. Phys Med. 2020. PMID: 31918375

10

A physics-guided modular deep-learning based automated framework for tumor segmentation in PET.

Leung KH, Marashdeh W, Wray R, Ashrafinia S, Pomper MG, Rahmim A, Jha AK. Leung KH, et al. Among authors: rahmim a. Phys Med Biol. 2020 Dec 18;65(24):245032. doi: 10.1088/1361-6560/ab8535. Phys Med Biol. 2020. PMID: 32235059

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