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- D. G. Black, Y. Oloumi Yazdi, J. Wong, R. Fedrigo, C. Uribe, D. J. Kadrmas, A. Rahmim, and I. S. Klyuzhin
Design of an Anthropomorphic PET Phantom with Elastic Lungs and Respiration Modeling
Medical Physics, Accepted for Publications, 2021.
- X. Hou, J. Brosch, C. Uribe, A. Desy, G. Böning, J-M. Beauregard, A. Celler, and A. Rahmim
Feasibility of single-time-point dosimetry for radiopharmaceutical therapies
J. Nucl. Med., In Press, 2021.
- M. R. Salmanpour, M. Shamsaei, and A. Rahmim
Feature selection and machine learning methods for optimal identification and prediction of subtypes in Parkinson’s disease
Comp. Meth. Prog. Biomed., Accepted for Publication, 2021.
- I. Shiri et al.
Machine learning-based prognostic modeling using clinical data and quantitative radiomic features from chest CT images in COVID-19 patients
Comp. Biol. Med., In Press, 2021.
- R. L. Wahl et al.
Mars Shot for nuclear medicine, molecular imaging, and molecularly targeted radiopharmaceutical therapy
J. Nucl. Med., vo. 62, pp. 6-14, 2021.
- J. Brosch, C. Uribe et al.
Influence of dosimetry method on bone lesion absorbed dose estimates in PSMA therapy: application to mCRPC patients receiving Lu-177-PSMA-I&T
EJNMMI Physics, In Press, 2021.
- M. Adams, A. Rahmim, and J. Tang
Improved motor outcome prediction in Parkinson’s disease applying deep learning to DaTscan SPECT images
Comp. Biol. Med., In Press, 2021.
- D. Du, J. Gu, X. Chen, W. Lv, Q. Feng, A. Rahmim, H. Wu, and L. Lu
Integration of PET/CT radiomics and semantic features for differentiation between active pulmonary tuberculosis and lung cancer
Molec. Imag. Biol., In Press, 2021.
- M. R. Salmanpour, M. Shamsaei, A. Saberi, G. Hajianfar, H. Soltanian-Zadeh, and A. Rahmim
Robust identification of Parkinson’s disease subtypes using radiomics and hybrid machine learning
Comp. Biol. Med., vol. 129, pp. 104142, 2021.
- J-C. Cheng, C. Bevington, A. Rahmim, I. Klyuzhin, J. Matthews, R. Boellaard, and V. Sossi
Dynamic PET image reconstruction utilizing intrinsic data-driven HYPR4D de-noising kernel
Med. Phys., In Press, 2021.
- G. Wang, A. Rahmim, and R. N. Gunn
PET parametric imaging: past, present, and future
IEEE Trans. Rad. Plas. Med. Sci., vol. 4, pp. 663 – 675, 2020.
- R. Samimi, A. Kamali-Asl, P. Geramifar, J. van den Hoff, and A. Rahmim
Short-duration dynamic FDG PET imaging: optimization and clinical application
Physica Medica, vol. 80, pp. 193-200, 2020.
- H. M. K. McGillivray, C. F. Uribe, A. Rahmim, M. M. Muermann, and R. J. Wassersug
From diagnostics to theranostics—and why better cancer care will always be costly
BC Med. Journal, vol. 62, pp. 373-379, 2020.
- X. Hou, H. Ma, P. L. Esquinas, C. F. Uribe, S. Tolhurst, F. Bénard, D. Liu, A. Rahmim, and A. Celler
Impact of image reconstruction method on dose distributions derived from 90Y PET images: phantom and liver radioembolization patient studies
Phys. Med. Biol., vol. 65, pp. 215022, 2020.
- I. Shiri, H. Abdollahi, M. R. Atashzar, A. Rahmim, and H. Zaidi
A theranostic approach based on radiolabeled antiviral drugs, antibodies and CRISPR associated proteins for early detection and treatment of SARS-CoV-2 disease
Nucl. Med. Comm., vol. 41, pp. 837-840, 2020.
- I. Shiri, G. Hajianfar, A. Sohrabi, H. Abdollahi, S. P. Shayesteh, P. Geramifar, H. Zaidi, M. Oveisi, and A. Rahmim
Repeatability of radiomic features in magnetic resonance imaging of glioblastoma: test-retest and image registration analyses
Med. Phys., vol. 47, pp. 4265-4280, 2020.
- H. Abdollahi, I. Shiri, J. J. Bevelacqua, A. Jafarzadeh, A. Rahmim, H. Zaidi, S. A. R. Mortazavi, and S. M. J. Mortazavi
Low dose radiation therapy and convalescent plasma: how a hybrid method may maximize benefits for COVID-19 patients
J. Biomed. Phys. Eng., vol. 10, pp. 387-394, 2020.
- I. Shiri, H. Arabi, P. Geramifar, G. Hajianfar, P. Ghafarian, A. Rahmim, M. R. Ay, and H. Zaidi
Deep-JASC: joint attenuation and scatter correction in whole-body 18F-FDG PET using a deep residual network
Euro. J. Nucl. Med. Mol. Imag., vol. 47, pp. 2533–2548, 2020.
- K. H. Leung, W. Marashdeh, R. Wray, S. Ashrafinia, M. G. Pomper, A. Rahmim, and A. K. Jha
A physics-guided modular deep-learning based automated framework for tumor segmentation in PET
Med. Phys. Biol, vol. 65, pp. 245032, 2020.
- I. Shiri, H. Maleki, G. Hajianfar, H. Abdollahi, S. Ashrafinia, M. Hatt, H. Zaidi, M. Oveisi, and A. Rahmim
Next generation radiogenomics sequencing for prediction of EGFR and KRAS mutation status in NSCLC patients using multimodal imaging and machine learning algorithms
Med. Imag. Biol, vol. 22, pp. 1132-1148, 2020.
- A. Zwanenburg et al.
The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping
Radiology, vol. 295, pp. 328–338, 2020.
- M. McNitt-Gray et al.
Standardization in quantitative imaging: a multi-center comparison of radiomics features from different software packages on digital reference objects and patient datasets
Tomography, vol. 6, pp. 118-128, 2020.
- M. Soltani, M. Jabbarifar, F. Moradi, and A. Rahmim
Evaluation of inverse methods for estimation of mechanical parameters in solid tumors
Biomed. Phys. Eng. Exp., vol. 6, pp. 035027, 2020.
- J. Kang et al.
Transcranial photoacoustic imaging of NMDA-evoked focal circuit dynamics in the rat hippocampus
J. Neural Eng., vol. 17, pp. 025001, 2020.
- W. Lv, S. Ashrafinia, J. Ma, L. Lu, and A. Rahmim
Multi-level multi-modality fusion radiomics: application to PET and CT imaging for prognostication of head and neck cancer
IEEE J. Biomed. Health Informatics, vol. 24, pp. 2268-2277, 2020.
- M. R. Salmanpour, M. Shamsaei, A. Saberi, I. S. Klyuzhin, J. Tang, V. Sossi, and A. Rahmim
Machine learning methods for optimal prediction of motor outcome in Parkinson’s disease
Physica Medica, vol. 69, pp. 233-240, 2020.
- D. Du, H. Feng, W. Lv, S. Ashrafinia, Q. Yuan, Q. Wang, W. Yang, Q. Feng, W. Chen, A. Rahmim, and L. Lu
Machine learning methods for optimal radiomics-based differentiation between recurrence and inflammation: application to nasopharyngeal carcinoma post-therapy PET/CT images
Molec. Imag. Biol., vol. 22, pp. 730–738, 2020.
- S. Rezaei, P. Ghafarian, M. Bakhshayesh-Karam, C. F. Uribe, A. Rahmim, S. Sarkar, and M. R. Ay
The impact of iterative reconstruction protocol, signal-to-background ratio and background activity on measurement of PET spatial resolution
Japanese J. Radiology, vol. 38, pp. 231–239, 2020.
- G. Mahmoudi, M. R. Ay, A. Rahmim, and H. Ghadiri
Computationally efficient system matrix calculation techniques in computed tomography iterative reconstruction
J. Med. Sign. Sens., vol. 10, pp. 1-11, 2020.
- S. P. Rowe, L. B. Solnes, Y. Yin, G. Kitchen, M. A. Lodge, N. A. Karakatsanis, A. Rahmim, M. G. Pomper, and J. P. Leal
Imager-4D: New software for viewing dynamic PET scans and extracting radiomic parameters from PET data
J. Digit. Imag., vol. 32, pp. 1071–1080, 2019.
- M. R. Salmanpour, M. Shamsaei, A. Saberi, S. Setayeshi, I. S. Klyuzhin, V. Sossi, and A. Rahmim
Optimized machine learning methods for prediction of cognitive outcome in Parkinson’s disease
Comp. Biol. Med., vol. 111, pp. 103347, 2019.
- S. Rezaei, P. Ghafarian, A. K. Jha, A. Rahmim, S. Sarkar, and M. R. Ay
Joint compensation of motion and partial volume effects by iterative deconvolution method associated with wavelet-based denoising in oncologic PET/CT imaging
Physica Medica, vol. 68, pp. 52-60, 2019.
- N. Ahmadi, A. Karimian, M. N. Nasrabadi, and A. Rahmim
Assessment of fetal and maternal radiation absorbed dose in 18F-FDG PET imaging
Intern. J. Rad. Res., vol. 17, pp. 651-657, 2019.
- G. Mahmoudi, M. R. Fouladi, M. R. Ay, A. Rahmim, and H. Ghadiri
Sparse-view statistical image reconstruction with improved total variation regularization for X-ray micro-CT imaging
J. Instrumentation, vol. 14, pp. P08023, 2019.
- I. Shiri, P. Ghafarian, P. Geramifar, K. H. Leung, M. Ghelichoghli, M. Oveisi, A. Rahmim, and M. R. Ay
Direct attenuation correction of brain PET images using only Emission data via a deep convolutional encoder-decoder (Deep-DAC)
European Radiology, vol. 29, pp. 6867-6879, 2019.
- J. Kang et al.
Transcranial recording of electrophysiological neural activity in the rodent brain in vivo using functional photoacoustic imaging of near-infrared voltage-sensitive dye
Frontiers in Neuroscience, vol. 13, 579, 2019.
- A. Rahmim, M. A. Lodge, N. A. Karakatsanis, V. Y. Panin, Y, Zhou, A. McMillan, S. Cho, H. Zaidi, M. E. Casey, and R. L. Wahl
Dynamic whole-body PET imaging: principles, potentials and applications
Euro. J. Nucl. Med. Mol. Imag., vol. 46, pp. 501–518, 2019.
- J. Tang, B. Yang, N. N. Shenkov, I. S. Klyuzhin, S. Fotouhi, E. Davoodi-Bojd, L. Lu, H. Soltanian-Zadeh, V. Sossi, and A. Rahmim
Artificial neural network based prediction of outcome in Parkinson’s disease patients using DaTscan SPECT imaging features
Med. Imag. Biol, vol. 21, pp. 1165-1173, 2019.
- A. Rahmim, K. P. Bak-Fredslund, S. Ashrafinia, L. Lu, C. R. Schmidtlein, R. M. Subramaniam, A. Morsing, S. Keiding, J. Horsager, and O. L. Munk
Prognostic modeling for patients with colorectal liver metastases incorporating FDG PET radiomic features
Euro. J. Radiol., vol. 113, pp. 101-109, 2019.
- W. Lv, Q. Yuan, Q. Wang, J. Ma, Q. Feng, W. Chen, A. Rahmim, and L. Lu
Radiomics analysis of PET and CT components of PET/CT imaging integrated with clinical parameters: application to prognosis for nasopharyngeal carcinoma
Mol. Imag. Biol, vol. 21, pp. 954-964, 2019.
- A. Ketabi, P. Ghafarian, M. A. Mosleh-Shirazi, S. R. Mahdavi, A. Rahmim, and M. R. Ay
Impact of image reconstruction methods on quantitative accuracy and variability of FDG-PET volumetric and textural measures in solid tumors
Euro. Radiol., vol. 29, pp. 2146–2156, 2019.
- I. S. Klyuzhin, J. F. Fu, N. Shenkov, A. Rahmim, and V. Sossi
Use of generative disease models for analysis and selection of radiomic features in PET
IEEE Trans. Rad. Plas. Med. Sci., vol. 3, pp. 178-191, 2019.
- I. S. Klyuzhin, J. F. Fu, A. Hong, M. Sacheli, N. Shenkov, M. Matarazzo, A. Rahmim, A. J. Stoessl, and V. Sossi
Data-driven, voxel-based analysis of brain PET images: application of PCA and LASSO Methods to visualize and quantify patterns of neurodegeneration
PLoS ONE, vol. 13, pp. e0206607, 2018.
- S. Shojaeilangari, C. R. Schmidtlein, A. Rahmim, and M. R. Ay
Recovery of missing data in partial geometry PET scanners: compensation in projection space versus image space
Med. Phys, vol. 45, pp. 5437-5449, 2018.
- Y. Zhu, A. K. Jha, D. F. Wong, and A. Rahmim
Image reconstruction in fluorescence molecular tomography with sparsity-initialized maximum-likelihood expectation maximization
Biomed. Opt. Exp., vol. 9, pp. 3106-3121, 2018.
- M. A. Lodge, J. P. Leal, A. Rahmim, J. J. Sunderland, and E. C. Frey
Measuring PET spatial resolution using a cylinder phantom positioned at an oblique angle
J. Nucl. Med., vol. 59, pp. 1768-1775, 2018.
- N. Salehi, A. Rahmim, E. Fatemizadeh, A. Akbarzadeh, M. H. Farahani, S. Farzanefar, and M. R. Ay
Cardiac contraction motion compensation in gated myocardial perfusion SPECT: A comparative study
Physica Medica, vol. 49, pp. 77-82, 2018.
- H. Ghadiri, M. R. Fouladi, and A. Rahmim
An analysis scheme for investigation of effects of various parameters on signals in acoustic-resolution photoacoustic microscopy of mice brain: a simulation study
Frontiers in Biomed. Tech., vol. 4, pp. 59-69, 2018.
- W. Lv, Q. Yuan, Q. Wang, J. Ma, J. Jiang, W. Yang, Q. Feng, W. Chen, A. Rahmim, and L. Lu
Robustness versus disease differentiation when varying parameter settings in radiomics features: application to nasopharyngeal PET/CT
Euro. Radiol., vol. 8, pp. 3245–3254, 2018.
- A. K. Jha, Y. Zhu, S. Arridge, D. F. Wong, and A. Rahmim
Incorporating reflection boundary conditions in the Neumann series radiative transport equation: application to photon propagation and reconstruction in diffuse optical imaging
Biomed. Opt. Exp., vol. 9, pp. 1389-1407, 2018.
- N. Ahmadi, M. N. Nasrabadi, A. Karimian, and A. Rahmim
Estimation of fetal absorbed dose from low-dose attenuation-correction CT in PET/CT imaging by using the Body Builder Phantom
Iranian J. Rad. Safety & Meas., vol. 6, pp. 45-53, 2018.
- A. Emami, H. Ghadiri, A. Rahmim, and M. R. Ay
A novel dual energy method for enhanced quantitative computed tomography
J. Instrumentation, vol. 13, pp. P01030, 2018.
- Z. Etemadi, P. Ghafarian, A. Bitarafan-Rajabi, H. Malek, A. Rahmim, and M. R. Ay
Is correction for metallic artefacts mandatory in cardiac SPECT/CT imaging in the presence of pacemaker and implantable cardioverter defibrillator leads?
Iranian J. Nucl. Med., vol. 26, pp. 35-46, 2018.
- L. Lu, X. Ma, H. Mohy-ud-Din, J. Ma, Q. Feng, A. Rahmim, and W. Chen
Enhancement of dynamic myocardial perfusion PET images based on low-rank plus sparse decomposition
Comp. Meth. Prog. Biomed., vol. 154, p. 57-69, 2018.
- A. Rahmim, P. Huang, N. Shenkov, S. Fotouhi, E. Davoodi-Bojd, L. Lu, Z. Mari, H. Soltanian-Zadeh, and V. Sossi
Improved prediction of outcome in Parkinson’s disease using radiomics analysis of longitudinal DAT SPECT Images (supplement)
NeuroImage: Clinical, vol. 16, pp. 539-544, 2017.
- R. Sharifpour, P. Ghafarian, A. Rahmim, and M. R. Ay
Quantification and reduction of respiratory induced artifacts in positron emission tomography/computed tomography using the time-of-flight technique
Nucl. Med. Comm., vol. 38, pp. 948–955, 2017.
- M. Khazaee, A. Kamali-Asl, P. Geramifar, and A. Rahmim
Low-dose 90Y PET/CT imaging optimized for lesion detectability and quantitative accuracy: a phantom study to assess feasibility of pre-therapy imaging to plan therapeutic dose
Nucl. Med. Comm., vol. 38, pp. 985–997, 2017.
- R. F. Gottesman et al.
Association between midlife vascular risk factors and estimated brain amyloid deposition
JAMA, vol. 317, pp. 1443-1450, 2017.
- S. Ashrafinia, H. Mohy-ud-Din, N. A. Karakatsanis, A. K. Jha, M. Casey, D. J. Kadrmas, and A. Rahmim
Generalized PSF modeling for optimized quantitation in PET imaging
Phys. Med. Biol., vol. 62, pp. 5149-5179, 2017.
- I. Shiri, A. Rahmim, P. Ghaffarian, P. Geramifar, H. Abdollahi, and A. Bitarafan-Rajabi
The impact of image reconstruction settings on 18F-FDG PET radiomic features: multi-scanner phantom and patient studies
European Radiology, vol. 27, pp. 4498-4509, 2017.
- B. A. Anderson, H. Kuwabara, D. F. Wong, J. Roberts, A. Rahmim, J. R. Brasic, and S. M. Courtney
Linking dopaminergic reward signals to the development of attentional bias: a positron emission tomographic study
NeuroImage, vol. 157, pp. 27-33, 2017.
- H. K. Zhang, P. Yan, J. Kang, D. Abou, H. N. D. Le, A. K. Jha, D. Thorek, J. Kang, A. Rahmim, D. F. Wong, E. M. Boctor, and L. M. Loew
Listening to membrane potential: photoacoustic voltage-sensitive dye recording
J. Biomed. Optics, vol. 22, pp. 045006, 2017.
- J. Tang, X. Wang, X. Gao, P. Segars, M. Lodge, and A. Rahmim
Enhancing ejection fraction measurement through 4D respiratory motion compensation in cardiac PET imaging (also see featured news article @ medicalphysicsweb)
Phys. Med. Biol., vol. 62, pp. 4496–4513, 2017.
- N. Ahmadi, M. N. Nasrabadi, A. Karimian, and A. Rahmim
A TLD based method to estimate bowtie filter shape in PET/CT
Intern. J. Rad. Res., vol. 15, pp. 383-390, 2017.
- S. K. Gerdekoohi, N. Vosoughi, K. Tanha, M. Asadi, P. Ghafarian, A. Rahmim, and M. R. Ay
Implementation of absolute quantification in small-animal SPECT imaging: phantom and animal studies
J. Appl. Clin. Med. Phys., vol. 18, pp. 215-223, 2017.
- P. Knoll, A. Rahmim, S. Gültekin, M. Samal, M. Ljungberg, S. Mirzaei, P. Segars, and B. Szczupak
Improved scatter correction with factor analysis for planar and SPECT imaging
Rev. Sci. Instrum., vol. 88, pp. 094303, 2017.
- J. Tang, X. Wang, and A. Rahmim
MRI assisted dual motion correction for myocardial perfusion defect detection in PET imaging
Med. Phys., vol. 44, pp. 4536-4547, 2017.
- A. K. Jha, E. Mena, B. Caffo, S. Ashrafinia, A. Rahmim, E. Frey, and R. M. Subramaniam
A practical no-gold-standard evaluation framework for quantitative imaging methods: application to lesion segmentation in PET
J. Med. Imag., vol. 4, pp. 011011, 2017.
- E. Mena, M. Taghipour, S. Sheikhbahaei, A. K. Jha, A. Rahmim, L. Solnes, and R. M. Subramaniam
Value of intratumoral metabolic heterogeneity and quantitative 18F-FDG PET/CT parameters to predict prognosis in patients with HPV-positive primary oropharyngeal squamous cell carcinoma
Clinic. Nucl. Med., vol. 42, p. e227-e234, 2017.
- M. Soltani, M. Sefidgar, H. Bazmara, M. E. Casey, R. M. Subramaniam, R. L. Wahl, and A. Rahmim
Spatiotemporal distribution modeling of PET tracer uptake in solid tumors
Ann. Nucl. Med., vol. 31, pp. 109-124, 2017.
- N. Zeraatkar, A. Rahmim, S. Sarkar, and M. R. Ay
Development and evaluation of image reconstruction algorithms for a novel desktop SPECT system
Asia Oceania J. Nucl. Med. Biol., vol. 5, pp. 120-133, 2017.
- M. Soufi, A. Kamali-Asl, P. Geramifar, and A. Rahmim
A novel framework for automated segmentation and labeling of homogeneous versus heterogeneous lung tumors in [18F]FDG PET imaging
Molec. Imag. Biol., vol. 19, pp. 456-468, 2017.
- A. Rahmim, Y. Salimpour, S. Jain, S. Blinder, I. S. Klyuzhin, G. S. Smith, Z. Mari, and V. Sossi
Application of texture analysis to DAT SPECT imaging: relationship to clinical assessments
NeuroImage: Clinical, vol. 12, pp. e1-e9, 2016.
- R. F. Gottesman et al.
The ARIC-PET amyloid imaging study: brain amyloid differences by age, race, sex, and APOE (supplement; also see editorial @ Neurology)
Neurology, vol. 87, pp. 473-480, 2016.
- L. Lu, W. Lv, J. Jiang, J. Ma, Q. Feng, A. Rahmim, and W. Chen
Robustness of radiomic features in [11C]Choline and [18F]FDG PET/CT imaging of nasopharyngeal carcinoma: impact of segmentation and discretization (supplement)
Molec. Imag. Biol., vol. 18, pp. 935-945, 2016.
- N. A. Karakatsanis, M. E. Casey, M. A. Lodge, A. Rahmim, and H. Zaidi
Whole-body direct 4D parametric PET imaging employing nested generalized Patlak expectation-maximization reconstruction (also see 1- featured news article @ medicalphysicsweb; 2- top 10 most popular PMB articles in 2016)
Phys. Med. Biol., vol. 61, pp. 5456–5485, 2016.
- F. Aalamifar, R. Seifabadi, M. Bernardo, Ayele H. Negussie, B. Turkbey, M. Merino, P. Pinto, A. Rahmim, B. J. Wood, and E. M. Boctor
Ultrasound tomosynthesis: a new paradigm for quantitative imaging of the prostate
Medical Image Computing and Computer Assisted Intervention (MICCAI), pp. 577-584, 2016.
- N. Zeraatkar, M. H. Farahani, A. Rahmim, S. Sarkar, and M. R. Ay
Design and assessment of a novel SPECT system for desktop open-gantry imaging of small animals: a simulation study
Med. Phys., vol. 43, pp. 2581-2597, 2016.
- A. Rahmim, C. R. Schmidtlein, A. Jackson, S. Sheikhbahaei, C. Marcus, S. Ashrafinia, M. Soltani, and R. M. Subramaniam
A novel metric for quantification of homogeneous and heterogeneous tumors in PET for enhanced clinical outcome prediction
Phys. Med. Biol., vol. 61, pp. 227-242, 2016.
- M. Soufi, A. R. Kamali-Asl, P. Geramifar, M. Abdoli, and A. Rahmim
Combined fuzzy logic and random walker algorithm for PET image tumor delineation
Nucl. Med. Comm., vol. 37, 171-181, 2016.
- B. A. Anderson, H. Kuwabara, D. F. Wong, E. G. Gean, A. Rahmim, J R. Brasic , N. George, B. Frolov, S. M. Courtney, and S. Yantis
The role of dopamine in value-based attentional orienting (also see commentary @ Johns Hopkins Magazine)
Current Biology, vol. 26, pp. 550-555, 2016.
- S. Sheikhbahaei, R. Wray, B. Young, E. Mena, M. Taghipour, A. Rahmim, and R. M. Subramaniam
18F-FDG-PET/CT therapy assessment of locally advanced pancreatic adenocarcinoma: impact on management and utilization of quantitative parameters for patient survival prediction
Nucl. Med. Comm., vol. 37, pp. 231-238, 2016.
- S. Sheikhbahaei, C. Marcus, R. Wray, A. Rahmim, M. A. Lodge, and R. M. Subramaniam
Impact of point-spread function reconstruction on quantitative 18F-FDG-PET/CT imaging parameters and inter-reader reproducibility in solid tumors
Nucl. Med. Comm., vol. 37, pp. 288-296, 2016.
- H. Bazmara, M. Soltani, M. Sefidgar, M. Bazargan, M. Mousavi, A. Rahmim
Blood flow and endothelial cell phenotype regulation during sprouting angiogenesis
Med. Biol. Eng. Comp., vol. 54, pp. 547-558, 2016.
- R. Wray, C. Marcus, S. Sheikhbahaei, E. Zan, R. Ferraro, A. Rahmim, and R. M. Subramaniam
Therapy response assessment and patient outcomes in head and neck squamous cell carcinoma: FDG PET Hopkins criteria versus residual neck node size and morphologic features
Am. J. Roentgenology, vol. 207, pp. 641-647, 2016.
- N. A. Karakatsanis, Y. Zhou, M. A. Lodge, M. E. Casey, R. L. Wahl, H. Zaidi, and A. Rahmim
Generalized whole-body Patlak parametric imaging for enhanced quantification in clinical PET
Phys. Med. Biol., vol. 40, pp. 8643-8673, 2015.
- H. Mohy-ud-Din, M. A. Lodge, and A. Rahmim
Quantitative myocardial perfusion PET parametric imaging at the voxel-level
Phys. Med. Biol., vol. 60, pp. 6013-6037, 2015.
- H. Mohy-ud-Din, N. A. Karakatsanis, W. Willis, A. K. Tahari, D. F. Wong, and A. Rahmim
Intra-frame motion compensation in multi-frame brain PET imaging
Frontiers in Biomed. Tech., vol. 2, pp. 366-379, 2015.
- C. Marcus, A. Antoniou, A. Rahmim, P. Ladenson, and and R. M. Subramaniam
Fluorodeoxyglucose positron emission tomography/computerized tomography in differentiated thyroid cancer management: Importance of clinical justification and value in predicting survival
J. Med. Imag. Rad. Onc., vol. 59, 281-288, 2015.
- J. Hossain, Y. Du, J. Links, A. Rahmim, N. Karakatsanis, A. Akhbardeh, J. Lyons, and E. Frey
Estimation of dynamic time activity curves from dynamic cardiac SPECT imaging
Phys. Med. Biol., vol. 60, pp. 3193-3208, 2015.
- H. Bazmara, M. Soltani, M. Sefidgar, M. Bazargan, M. Mousavi, A. Rahmim
The vital role of blood flow-induced proliferation and migration in capillary network formation in a multiscale model of angiogenesis
PLoS ONE, vol. 10, pp. e0128878, 2015.
- L. Lu, J. Ma, Q. Feng, W. Chen, and A. Rahmim
Anatomy-guided brain PET imaging incorporating a joint prior model
Phys. Med. Biol., vol. 60, pp. 2145-66, 2015.
- J. Tang and A. Rahmim
Anatomy assisted PET image reconstruction incorporating multi-resolution joint entropy
Phys. Med. Biol., vol. 60, pp. 31-48, 2015.