31 citations · 68 across the 13 of their papers we have counts for
13 papers
Accelerating Stroke MRI with Diffusion Probabilistic Models through Large-Scale Pre-training and Target-Specific Fine-Tuning
Yamin Arefeen, Sidharth Kumar, Steven Warach +2
Purpose: To develop a data-efficient strategy for accelerated MRI reconstruction with Diffusion Probabilistic Generative Models (DPMs) that enables faster scan times in clinical st…
Theoretical Bounds on Parallel Imaging Implicit Data Crimes in an MRI Reproducing Kernel Hilbert Space
Evan Frenklak, Yamin Arefeen, Jonathan I Tamir
Magnetic Resonance Imaging (MRI) diagnoses and manages a wide range of diseases, yet long scan times drive high costs and limit accessibility. AI methods have demonstrated substant…
Diffusion Probabilistic Generative Models for Accelerated, in-NICU Permanent Magnet Neonatal MRI
Yamin Arefeen, Brett Levac, Bhairav Patel +2
Purpose: Magnetic Resonance Imaging (MRI) enables non-invasive assessment of brain abnormalities during early life development. Permanent magnet scanners operating in the neonatal…
Robust multi-coil MRI reconstruction via self-supervised denoising
Asad Aali, Marius Arvinte, Sidharth Kumar +2
We study the effect of incorporating self-supervised denoising as a pre-processing step for training deep learning (DL) based reconstruction methods on data corrupted by Gaussian n…
A Generative Diffusion Model to Solve Inverse Problems for Robust in-NICU Neonatal MRI
Yamin Arefeen, Brett Levac, Jonathan I. Tamir
We present the first acquisition-agnostic diffusion generative model for Magnetic Resonance Imaging (MRI) in the neonatal intensive care unit (NICU) to solve a range of inverse pro…
INFusion: Diffusion Regularized Implicit Neural Representations for 2D and 3D accelerated MRI reconstruction
Yamin Arefeen, Brett Levac, Zach Stoebner +1
Implicit Neural Representations (INRs) are a learning-based approach to accelerate Magnetic Resonance Imaging (MRI) acquisitions, particularly in scan-specific settings when only d…
A dataset and benchmark for hospital course summarization with adapted large language models
Asad Aali, Dave Van Veen, Yamin Ishraq Arefeen +9
Brief hospital course (BHC) summaries are clinical documents that summarize a patient's hospital stay. While large language models (LLMs) depict remarkable capabilities in automati…
SubZero: Subspace Zero-Shot MRI Reconstruction
Heng Yu, Yamin Arefeen, Berkin Bilgic
Recently introduced zero-shot self-supervised learning (ZS-SSL) has shown potential in accelerated MRI in a scan-specific scenario, which enabled high-quality reconstructions witho…
Zero-DeepSub: Zero-Shot Deep Subspace Reconstruction for Rapid Multiparametric Quantitative MRI Using 3D-QALAS
Yohan Jun, Yamin Arefeen, Jaejin Cho +7
Purpose: To develop and evaluate methods for 1) reconstructing 3D-quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) time-ser…
Optimizing Sampling Patterns for Compressed Sensing MRI with Diffusion Generative Models
Sriram Ravula, Brett Levac, Yamin Arefeen +3
Magnetic resonance imaging (MRI) is a powerful medical imaging modality, but long acquisition times limit throughput, patient comfort, and clinical accessibility. Diffusion-based g…
Zero-Shot Self-Supervised Joint Temporal Image and Sensitivity Map Reconstruction via Linear Latent Space
Molin Zhang, Junshen Xu, Yamin Arefeen +1
Fast spin-echo (FSE) pulse sequences for Magnetic Resonance Imaging (MRI) offer important imaging contrast in clinically feasible scan times. T2-shuffling is widely used to resolve…
Predicting Critical Biogeochemistry of the Southern Ocean for Climate Monitoring
Ellen Park, Jae Deok Kim, Nadege Aoki +5
The Biogeochemical-Argo (BGC-Argo) program is building a network of globally distributed, sensor-equipped robotic profiling floats, improving our understanding of the climate syste…
Image2Lego: Customized LEGO Set Generation from Images
Kyle Lennon, Katharina Fransen, Alexander O'Brien +5
Although LEGO sets have entertained generations of children and adults, the challenge of designing customized builds matching the complexity of real-world or imagined scenes remain…