58 citations · 143 across the 40 of their papers we have counts for
30 papers · 1 filter
Progress in SPECT and PET Reconstruction for Theranostics: From Diagnosis to Therapy
Kweku Enninful, Fardeen Ahmed, Bradley Girod +4
The theranostic paradigm enables personalization of treatment by selecting patients with a diagnostic radiopharmaceutical and monitoring therapy using a matched therapeutic isotope…
Development and in silico imaging trial evaluation of a deep-learning-based transmission-less attenuation compensation method for DaT SPECT
Zitong Yu, Md Ashequr Rahman, Zekun Li +7
Quantitative measures of dopamine transporter (DaT) uptake in caudate, putamen, and globus pallidus derived from DaT-single-photon emission computed tomography (SPECT) images are b…
ISIT-GEN: An in silico imaging trial to assess the inter-scanner generalizability of CTLESS for myocardial perfusion SPECT on defect-detection task
Zitong Yu, Nu Ri Choi, Zezhang Yang +3
A recently proposed scatter-window and deep learning-based attenuation compensation (AC) method for myocardial perfusion imaging (MPI) by single-photon emission computed tomography…
CTLESS: A scatter-window projection and deep learning-based transmission-less attenuation compensation method for myocardial perfusion SPECT
Zitong Yu, Md Ashequr Rahman, Craig K. Abbey +4
Attenuation compensation (AC), while being beneficial for visual-interpretation tasks in myocardial perfusion imaging (MPI) by SPECT, typically requires the availability of a separ…
Nuclear Medicine AI in Action: The Bethesda Report (AI Summit 2024)
Arman Rahmim, Tyler J. Bradshaw, Guido Davidzon +10
The 2nd SNMMI Artificial Intelligence (AI) Summit, organized by the SNMMI AI Task Force, took place in Bethesda, MD, on February 29 - March 1, 2024. Bringing together various commu…
Can patient-specific acquisition protocol improve performance on defect detection task in myocardial perfusion SPECT?
Nu Ri Choi, Md Ashequr Rahman, Zitong Yu +2
Myocardial perfusion imaging using single-photon emission computed tomography (SPECT), or myocardial perfusion SPECT (MPS) is a widely used clinical imaging modality for the diagno…
WIN-PDQ: A Wiener-estimator-based projection-domain quantitative SPECT method that accounts for intra-regional uptake heterogeneity
Zekun Li, Nadia Benabdallah, Daniel L. J. Thorek +1
SPECT can enable the quantification of activity uptake in lesions and at-risk organs in α-particle-emitting radiopharmaceutical therapies (α-RPTs). But this quantification is chall…
Observer study-based evaluation of TGAN architecture used to generate oncological PET images
Roberto Fedrigo, Fereshteh Yousefirizi, Ziping Liu +9
The application of computer-vision algorithms in medical imaging has increased rapidly in recent years. However, algorithm training is challenging due to limited sample sizes, lack…
DEMIST: A deep-learning-based task-specific denoising approach for myocardial perfusion SPECT
Md Ashequr Rahman, Zitong Yu, Richard Laforest +3
There is an important need for methods to process myocardial perfusion imaging (MPI) SPECT images acquired at lower radiation dose and/or acquisition time such that the processed i…
A list-mode multi-energy window low-count SPECT reconstruction method for isotopes with multiple emission peaks
Md Ashequr Rahman, Zekun Li, Zitong Yu +3
SPECT provides a mechanism to perform absorbed-dose quantification tasks for -particle radiopharmaceutical therapies (-RPTs). However, quantitative SPECT for -RPT is chall…
Joint regional uptake quantification of Thorium-227 and Radium-223 using a multiple-energy-window projection-domain quantitative SPECT method
Zekun Li, Nadia Benabdallah, Richard Laforest +3
Thorium-227-based alpha-particle radiopharmaceutical therapies (α-RPTs) are being investigated in several clinical and pre-clinical studies. After administration, Thorium-227 decay…
Development and task-based evaluation of a scatter-window projection and deep learning-based transmission-less attenuation compensation method for myocardial perfusion SPECT
Zitong Yu, Md Ashequr Rahman, Craig K. Abbey +2
Attenuation compensation (AC) is beneficial for visual interpretation tasks in single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). However, tradi…
Need for objective task-based evaluation of AI-based segmentation methods for quantitative PET
Ziping Liu, Joyce C. Mhlanga, Barry A. Siegel +1
Artificial intelligence (AI)-based methods are showing substantial promise in segmenting oncologic positron emission tomography (PET) images. For clinical translation of these meth…
Issues and Challenges in Applications of Artificial Intelligence to Nuclear Medicine -- The Bethesda Report (AI Summit 2022)
Arman Rahmim, Tyler J. Bradshaw, Irène Buvat +10
The SNMMI Artificial Intelligence (SNMMI-AI) Summit, organized by the SNMMI AI Task Force, took place in Bethesda, MD on March 21-22, 2022. It brought together various community me…
Ideal-observer computation with anthropomorphic phantoms using Markov Chain Monte Carlo
Md Ashequr Rahman, Zitong Yu, Abhinav K. Jha
In medical imaging, it is widely recognized that image quality should be objectively evaluated based on performance in clinical tasks. To evaluate performance in signal-detection t…
No-gold-standard evaluation of quantitative imaging methods in the presence of correlated noise
Ziping Liu, Zekun Li, Joyce C. Mhlanga +2
Objective evaluation of quantitative imaging (QI) methods with patient data is highly desirable, but is hindered by the lack or unreliability of an available gold standard. To addr…
Investigating the limited performance of a deep-learning-based SPECT denoising approach: An observer-study-based characterization
Zitong Yu, Md Ashequr Rahman, Abhinav K. Jha
Multiple objective assessment of image-quality-based studies have reported that several deep-learning-based denoising methods show limited performance on signal-detection tasks. Ou…
Objective task-based evaluation of artificial intelligence-based medical imaging methods: Framework, strategies and role of the physician
Abhinav K. Jha, Kyle J. Myers, Nancy A. Obuchowski +5
Artificial intelligence (AI)-based methods are showing promise in multiple medical-imaging applications. Thus, there is substantial interest in clinical translation of these method…
Toward High-Throughput Artificial Intelligence-Based Segmentation in Oncological PET Imaging
Fereshteh Yousefirizi, Abhinav K. Jha, Julia Brosch-Lenz +2
Artificial intelligence (AI) techniques for image-based segmentation have garnered much attention in recent years. Convolutional neural networks (CNNs) have shown impressive result…
A projection-domain low-count quantitative SPECT method for alpha-particle emitting radiopharmaceutical therapy
Zekun Li, Nadia Benabdallah, Diane S. Abou +9
Single-photon emission computed tomography (SPECT) provides a mechanism to estimate regional isotope uptake in lesions and at-risk organs after administration of α-particle-emittin…
A physics and learning-based transmission-less attenuation compensation method for SPECT
Zitong Yu, Md Ashequr Rahman, Thomas Schindler +2
Attenuation compensation (AC) is a pre-requisite for reliable quantification and beneficial for visual interpretation tasks in single-photon emission computed tomography (SPECT). T…
Task-based assessment of binned and list-mode SPECT systems
Md Ashequr Rahman, Abhinav K. Jha
In SPECT, list-mode (LM) format allows storing data at higher precision compared to binned data. There is significant interest in investigating whether this higher precision transl…
Observer study-based evaluation of a stochastic and physics-based method to generate oncological PET images
Ziping Liu, Richard Laforest, Joyce Mhlanga +5
Objective evaluation of new and improved methods for PET imaging requires access to images with ground truth, as can be obtained through simulation studies. However, for these stud…
A tissue-fraction estimation-based segmentation method for quantitative dopamine transporter SPECT
Ziping Liu, Hae Sol Moon, Zekun Li +4
Quantitative measures of dopamine transporter (DaT) uptake in caudate, putamen, and globus pallidus (GP) have potential as biomarkers for measuring the severity of Parkinson diseas…