These are only select journal articles and proceedings. For a complete list, please see the Pubmed link.

The papers posted here are for educational purposes only and adherence to copyright laws is assumed.

  • Z. Liu, H. Moon, Z. Li, R. Laforest, J. S. Perlmutter, S. A. Norris, A. K. Jha, “A tissue-fraction estimation-based segmentation method for quantitative dopamine transporter SPECT”, Med. Phys., 2022 (link) (arxiv) (Media coverage)
  • A. K. Jha, T. J. Bradshaw, I. Buvat, M. Hatt, P. KC, C. Liu, N. F. Obuchowski, B. Saboury, P. J. Slomka, J. J. Sunderland, R. L. Wahl, Z. Yu, S. Zuehlsdorff, A. Rahmim, and R. Boellaard, “Nuclear medicine and artificial intelligence: Best practices for evaluation (the RELAINCE guidelines),”, J. Nuc. Med., 2022 (open access link) (Media coverage)
  • Z. Li, N. Benabdallah, D. Abou, B. Baumann, R. Wahl, D. Thorek, A. K. Jha, “A projection-domain low-count quantitative SPECT method for alpha-particle emitting radiopharmaceutical therapy”, IEEE Trans. Rad. Plasma Sci., 2022 (link) (arxiv) (Media coverage)
  • A. K. Jha, K. J. Myers, N. A. Obuchowski, Z. Liu, M. A. Rahman, B. Saboury, A. Rahmim, B. A. Siegel, “Objective task-based evaluation of artificial intelligence-based medical imaging methods: Framework, strategies and role of the physician”, PET Clinics (special issue on AI in PET), 2021 (link) (arxiv) (Media coverage)
  • F Yousefirizi, A. K. Jha, J Brosch-Lenz, B Saboury, A Rahmim. “Toward High-Throughput Artificial Intelligence-Based Segmentation in Oncological PET Imaging”, PET Clin. 2021 Oct;16(4):577-596 (link) (arxiv).
  • N. Benabdallah, W. Scheve, N. Dunn, D. Silvestros, P. Schelker, D. Abou, U. Jammalamadaka, R. Laforest, Z. Li, J. Liu, D. H. Ballard, N. M. Maughan, H. Gay, B. C. Baumann, R. F. Hobbs, B. Rogers, A. Iravani, A. K. Jha, F. Dehdashti, D. L. J. Thorek, “Practical considerations for quantitative clinical SPECT/CT imaging of alpha particle emitting radioisotopes”, Theranostics, 2021 (link)
  • P Lu, N Benabdallah, W Jiang, B W Simons, H Zhang, R F Hobbs, D Ulmert, B Baumann, R K Pachynski, A K Jha, D L Thorek. “Blind Image Restoration Enhances Digital Autoradiographic Imaging of Radiopharmaceutical Tissue Distribution”, J Nucl Med. 2021 (link) (Journal cover)
  • K Dutta, S Roy, T D Whitehead, J Luo, A K Jha, S Li, J D Quirk, K I Shoghi. “Deep Learning Segmentation of Triple-Negative Breast Cancer (TNBC) Patient Derived Tumor Xenograft (PDX) and Sensitivity of Radiomic Pipeline to Tumor Probability Boundary”, Cancers (Basel). 2021 Jul 28;13(15):3795. (link)
  • Li, N. Benabdallah, D. Thorek, A. K. Jha, “A multiple-energy-window projection-domain quantitative SPECT method for joint regional uptake quantification of Th-227 and Ra-223”, Proceedings of the International Conference on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2021 (Oral Award Nominee)
  • Z. Liu, J. C. Mhlanga, R. Laforest, P. Derenoncourt, B. A. Siegel, A. K. Jha, A Bayesian approach to tissue-fraction estimation for oncological PET segmentation”, Phys. Med. Biol. 2021 (link) (arxiv) (Media coverage)
  • Liu, R. Laforest, J. Mhlanga, T. Fraum, M. Itani, F. Dehdashti, B. Siegel, A. K. Jha, “Observer study-based evaluation of a stochastic and physics-based method to generate oncological PET images”, Proceedings SPIE Medical Imaging, 2021 (link) (arxiv)
  • Yu, M. A. Rahman, R. Laforest, S. Norris, A. K. Jha, “A physics and learning-based transmission-less attenuation compensation method for SPECT”, Proceedings SPIE Medical Imaging 2021 (link) (arxiv)
  • A. Rahman, A. K. Jha, “Task-based assessment of binned and list-mode SPECT systems”, Proceedings SPIE Medical Imaging 2021 (link) (arxiv)
  • M. A. Rahman, Y. Zhu, E. Clarkson, M. Kupinski, E. Frey, A. K. Jha, Fisher information analysis of list-mode SPECT emission data for joint estimation of activity and attenuation distribution”, Inverse Problems, 2020 (link) (arxiv)
  • K. Leung, W. Marashdeh, R. Wray, S. Ashrafinia, M. Pomper. A. Rahmim, A. K. Jha, “A physics-guided modular deep-learning-based automated framework for tumor segmentation in PET”, Phys. Med. Biol., 2020, link (arxiv) (Media coverage) (Source code)
  • D S Abou, A Rittenbach, R E Tomlinson et al. “Preclinical Single Photon Emission Computed Tomography of Alpha Particle-Emitting Radium-223” Cancer Biother. Radiopharm 2020 (link)
  • A. Rahman, R. Laforest, A. K. Jha, “A list-mode OSEM-based attenuation and scatter compensation method for SPECT”, IEEE Symposium on Biomedical Imaging 2020 (link) (arxiv)
  • L. Caucci, Z. Liu, A. K. Jha, H. Han, L R Furenlid, H. H. Barrett, “Towards Continuous-to-Continuous 3D Imaging in the Real World”, Phys. Med. Biol., 18; 64(18), 2019 (link)
  • S. Rezaei, P. Ghafarian, A. K. Jha, A. Rahmim, S. Sarkar, M. R. Ay, “Joint compensation of motion and partial volume effects in oncologic PET/CT imaging”, vol. 68, 52-60, 2019 Phys. Med. (link)
  • Y. Zhu, A. K. Jha*, D. F. Wong, A. Rahmim, “Image reconstruction in fluorescence molecular tomography with sparsity-initialized maximum-likelihood expectation maximization”, Biomed. Opt. Exp. 9(7), 3106-21, 2018 (link) (*Corresponding author) (Source code)
  • A. K. Jha, Y. Zhu, S, Arridge, D. F. Wong, and A. Rahmim, “Incorporating reflection boundary conditions in radiative transport equation-based photon propagation and image reconstruction in diffuse optical imaging”, Biomed. Opt. Exp., 9 (4), 1389-1407, 2018 (link) (Source code)
  • Ye Li, S. O’Reilly, D. Plyku, S. T. Treves, Y. Du, F. Fahey, X. Cao, A. K. Jha, G. Sgouros, W. E. Bolch, and E. Frey, “A projection image database to investigate factors affecting image quality in weight-based dosing: Application to pediatric renal SPECT”, Phys. Med. Biol., 2018 (link).
  • A. K. Jha, E. Mena, B. Caffo, S. Ashrafinia, A. Rahmim, E. C. Frey and R. Subramaniam, “Practical no-gold-standard framework to evaluate quantitative imaging methods: Application to lesion segmentation in PET”, J. Med. Imag. , 2017 (Special Section on PET imaging), 4(1), 2017 (pdf).
  • F. E. A. Elshahaby, A. K. Jha, M. Ghaly, E. C. Frey, “A Comparison of Resampling Schemes for Estimating Model Observer Performance with Small Ensembles”, Phys. Med. Biol., 22;62(18):7300-7320, 2017 (pdf)
  • X. Li, A. K. Jha, M. Ghaly, F. E. A. Elshahaby, J. M. Links, E. C. Frey, “A Sub-ensemble-based approach for detection task performance evaluation for non-multivariate-normally distributed data using multi-template linear observer strategies”, IEEE Trans. Med. Imaging, 36(4), 2017 (pdf)
  • S. Ashrafinia, H. Mohy-ud-Din, N. Karakatsanis, A. K. Jha, M. Casey, D. Kadrmas; A. Rahmim, “Generalized PSF-Modelling for Optimized Quantitation in PET Imaging”, Phys. Med. Biol., 2017 (pdf)
  • E. Mena, M. Taghipour, S. Sheikhbahaei, A. K. Jha, L. Solnes, R. M. Subramaniam, “Value of intra-tumoral metabolic heterogeneity and quantitative 18F-FDG PET/CT parameters to predict prognosis, in patients with HPV-positive primary oropharyngeal squamous cell carcinoma”, Clin. Nuc. Med., 42(5); e227-34, 2017 (pdf)
  • A. K. Jha, Y. Zhu, D. F. Wong, A. Rahmim, “A radiative transfer equation-based image-reconstruction method incorporating boundary conditions for diffuse optical imaging”, SPIE Medical Imaging, 1013705-1013705- 2017 (link)
  • A. K. Jha and E. Frey, “No-gold-standard evaluation of image-acquisition methods using patient data”, SPIE Medical Imaging, 101360L-101360L-8, 2017 (link)
  • E. Mena, S. Sheikhbahaei, M. Taghipour, A. K. Jha, J. Xiao, E. Vicente, R. M. Subramaniam, “18F-FDG PET/CT Metabolic Tumor Volume and intra-tumoral heterogeneity: Impact of Dual-Time-Point and Segmentation Methods”, Clin. Nuc. Med., 42(1), e16-e21, 2017 (link)
  • A. K. Jha, J. J. Rodriguez, A. T. Stopeck, “A maximum-likelihood method to estimate a single ADC value of lesions using diffusion MRI”, Mag. Res. Med., 76(6), 2016 (pdf) (Directions to source code)
  • A. K. Jha, B. Caffo, E. Frey, “A no-gold-standard technique for objective assessment of quantitative nuclear-medicine imaging methods”, Phys. Med. Biol., 61(7), 2780-2800, 2016 (pdf)
  • F. E. A. Elshahaby, M. Ghaly, A. K. Jha, E. C. Frey, “Factors Affecting the Normality of Anthropomorphic Channel Outputs: An Investigation using Realistic Myocardial Perfusion SPECT Images”, J. Med. Imag., 3(1), 015503-1-17, 2016 (pdf)
  • R. M. Stephen, A. K. Jha, D. J. Roe, et al., “Diffusion MRI with Semi-Automated Segmentation Can Serve as a Restricted Predictive Biomarker of the Therapeutic Response of Liver Metastasis”, Magn. Res. Imag., 33(10), 1267-33, 2015 (pdf) (Directions to source code)
  • A. K. Jha, H. H. Barrett, E. Frey, E. Clarkson, L. Caucci, M. A. Kupinski, “Singular value decomposition for photon-processing nuclear imaging systems and applications for reconstruction and computing null functions”, Phys. Med. Biol., 60, 7359-7385, 2015 (link)
  • A. K. Jha and E. Frey, “Incorporating prior information in a no-gold-standard technique to assess quantitative SPECT reconstruction methods”, 13th Intl. Meet. Fully Three-Dim. Image Recon. Radiol. Nucl. Med, 2015 (pdf)
  • A. K. Jha, E. Frey, “Estimating ROI activity concentration with photon-processing and photon-counting SPECT systems”, SPIE Med. Imag. Conf. 2015 (link)
  • V. Bora, H. H. Barrett, A. K. Jha, E. Clarkson, “Impact of Fano factor on position and energy estimation in scintillation detectors”, IEEE Trans. Nucl. Sci., 99, pp. 11-15, 2015 (link).
  • A. K. Jha, E. Clarkson, M. A. Kupinski, “An ideal-observer framework to investigate signal detectability in diffuse optical imaging”, Biomed. Opt. Express, 4(10), 2107-23, 2013 (link) (Source code)
  • A. K. Jha, H. T. van Dam, M. A. Kupinski, E. Clarkson, “Simulating Silicon photomultiplier response to scintillation light”, IEEE Trans. Nucl. Sci., 60(1), 336-51, 2013 (link) (Source code)
  • A. K. Jha, M. A. Kupinski, H. H. Barrett, E. Clarkson, J. H. Hartman, “A three-dimensional Neumann-series approach to model light transport in non-uniform media”, J. Opt. Soc. Amer. A, 29(8), 1885-99, 2012 (link) (Source code)
  • A. K. Jha, M. A. Kupinski, T. Masumura, E. Clarkson, A. A. Maslov, H. H. Barrett, “Simulating photon transport in uniform media using the radiative transport equation: A study using the Neumann-series approach”, J. Opt. Soc. Amer. A, 29(8), 1741-1757, 2012. (Top 10 downloaded articles in Aug. 2012 edition) (link) (Source code)
  • A. K. Jha, M. A. Kupinski, J. J. Rodriguez, R. Stephen, A. Stopeck, “Task-based evaluation of segmentation algorithms for diffusion-weighted MRI without using a gold standard”, Phys. Med. Biol., 57(13) 4425-46, 2012 (link)
  • Y. Zhu, A. K. Jha*, J. K. Dreyer, H. Le, J. U. Kang, P. E. Roland, D. F. Wong, and A. Rahmim, “A three-step reconstruction method for fluorescence molecular tomography based on compressive sensing”, Proc. SPIE 10059, Optical Tomography and Spectroscopy of Tissue, 1005911, 2017 (*corresponding author) (link)
  • L. Caucci, A. K. Jha, L. R. Furenlid, E. W. Clarkson, M. A. Kupinski, H. H. Barrett, “Image science with photon-processing detectors”, IEEE Nucl. Sci. Symp. Med. Imag. Conf., 2013 (link)
  • A. K. Jha, H. H. Barrett, E. Clarkson, L. Caucci, M. A. Kupinski, “Analytic list-mode reconstruction techniques”, 12th Intl. Meet. Fully Three-Dim. Image Recon. Radiol. Nucl. Med, CA, June 2013 (pdf)
  • A. K. Jha, E. Clarkson, M. A. Kupinski, H. H. Barrett. “Joint reconstruction of activity and attenuation map using LM SPECT emission data”, Proc. SPIE 8668 Med. Imag., 86681W, 2013 (link)
  • Park, B. W. Miller, A. K. Jha, L. R. Furenlid, W. C. Hunter, H. H. Barrett, “A prototype detector for a novel high-resolution PET system: Bazooka PET”, IEEE Med Imag. Conf., 2012 (link)
  • A. K. Jha, J. J. Rodriguez, R. M. Stephen, A. T. Stopeck, “A clustering algorithm for liver lesion segmentation of diffusion-weighted MR images”, Proc. IEEE Southwest Symp. Image Anal. Interpret., pp. 93-6, 2010 (link)
  • A. K. Jha, M. A. Kupinski, J. J. Rodriguez, R. M. Stephen, A. T. Stopeck, “Evaluating segmentation algorithms for diffusion-weighted MR images: a task-based approach”, Proc. SPIE 7627,76270L1-8, 2010 (Best Student Paper Award) (link)