User profiles for Parham Geramifar
 | Parham GeramifarMedical Physicist Specialist in Nuclear Medicine Verified email at tums.ac.ir Cited by 1997 |
The impact of image reconstruction settings on 18F-FDG PET radiomic features: multi-scanner phantom and patient studies
Objectives The purpose of this study was to investigate the robustness of different PET/CT
image radiomic features over a wide range of different reconstruction settings. Methods …
image radiomic features over a wide range of different reconstruction settings. Methods …
[HTML][HTML] Machine learning-based prognostic modeling using clinical data and quantitative radiomic features from chest CT images in COVID-19 patients
Objective To develop prognostic models for survival (alive or deceased status) prediction of
COVID-19 patients using clinical data (demographics and history, laboratory tests, visual …
COVID-19 patients using clinical data (demographics and history, laboratory tests, visual …
[HTML][HTML] Controlling evolution of protein corona: A prosperous approach to improve chitosan-based nanoparticle biodistribution and half-life
Protein corona significantly affects in vivo fate of nanoparticles including biodistribution and
half-life. Without manipulating the physicochemical properties of nanoparticles with …
half-life. Without manipulating the physicochemical properties of nanoparticles with …
[HTML][HTML] COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14,339 patients
Background We aimed to analyze the prognostic power of CT-based radiomics models using
data of 14,339 COVID-19 patients. Methods Whole lung segmentations were performed …
data of 14,339 COVID-19 patients. Methods Whole lung segmentations were performed …
Deep-JASC: joint attenuation and scatter correction in whole-body 18F-FDG PET using a deep residual network
Objective We demonstrate the feasibility of direct generation of attenuation and scatter-corrected
images from uncorrected images (PET-nonASC) using deep residual networks in whole…
images from uncorrected images (PET-nonASC) using deep residual networks in whole…
Direct attenuation correction of brain PET images using only emission data via a deep convolutional encoder-decoder (Deep-DAC)
Objective To obtain attenuation-corrected PET images directly from non-attenuation-corrected
images using a convolutional encoder-decoder network. Methods Brain PET images from …
images using a convolutional encoder-decoder network. Methods Brain PET images from …
Targeted delivery system based on gemcitabine-loaded silk fibroin nanoparticles for lung cancer therapy
Here, a targeted delivery system was developed based on silk fibroin nanoparticles (SFNPs)
for the systemic delivery of gemcitabine (Gem) to treat induced lung tumor in a mice model. …
for the systemic delivery of gemcitabine (Gem) to treat induced lung tumor in a mice model. …
[HTML][HTML] Deep learning–based denoising of low-dose SPECT myocardial perfusion images: quantitative assessment and clinical performance
Purpose This work was set out to investigate the feasibility of dose reduction in SPECT
myocardial perfusion imaging (MPI) without sacrificing diagnostic accuracy. A deep learning …
myocardial perfusion imaging (MPI) without sacrificing diagnostic accuracy. A deep learning …
Repeatability of radiomic features in magnetic resonance imaging of glioblastoma: Test–retest and image registration analyses
…, H Abdollahi, S P. Shayesteh, P Geramifar… - Medical …, 2020 - Wiley Online Library
Purpose To assess the repeatability of radiomic features in magnetic resonance (MR)
imaging of glioblastoma (GBM) tumors with respect to test–retest, different image registration …
imaging of glioblastoma (GBM) tumors with respect to test–retest, different image registration …
Diagnosis of COVID-19 using CT image radiomics features: a comprehensive machine learning study involving 26,307 patients
Purpose To derive and validate an effective radiomics-based model for differentiation of
COVID-19 pneumonia from other lung diseases using a very large cohort of patients. Methods …
COVID-19 pneumonia from other lung diseases using a very large cohort of patients. Methods …