7 citations · 12 across the 13 of their papers we have counts for
16 papers
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…
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…
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…
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…
Need for Objective Task-based Evaluation of Deep Learning-Based Denoising Methods: A Study in the Context of Myocardial Perfusion SPECT
Zitong Yu, Md Ashequr Rahman, Richard Laforest +5
Artificial intelligence-based methods have generated substantial interest in nuclear medicine. An area of significant interest has been using deep-learning (DL)-based approaches fo…
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…
A task-specific deep-learning-based denoising approach for myocardial perfusion SPECT
Md Ashequr Rahman, Zitong Yu, Barry A. Siegel +1
Deep-learning (DL)-based methods have shown significant promise in denoising myocardial perfusion SPECT images acquired at low dose. For clinical application of these methods, eval…
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…
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…
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…
A list-mode OSEM-based attenuation and scatter compensation method for SPECT
Md Ashequr Rahman, Richard Laforest, Abhinav K. Jha
Reliable attenuation and scatter compensation (ASC) is a prerequisite for quantification and beneficial for visual interpretation tasks in SPECT. In this paper, we develop a recons…
Native Language Identification using i-vector
Ahmed Nazim Uddin, Md Ashequr Rahman, Md. Rafidul Islam +1
The task of determining a speaker's native language based only on his speeches in a second language is known as Native Language Identification or NLI. Due to its increasing applica…
Fisher information analysis of list-mode SPECT emission data for joint estimation of activity and attenuation distribution
Md Ashequr Rahman, Yansong Zhu, Eric Clarkson +3
The potential to perform attenuation and scatter compensation (ASC) in single-photon emission computed tomography (SPECT) imaging using only the SPECT emission data is highly signi…