Enhancing MRI Imaging Efficiency: A Hybrid Under-Sampling Strategy for k-Space Data Acquisition
Year: 2025
Type: conference-paper
Abstract: Compressed Sensing (CS) offers a promising solution to reduce MRI acquisition times, addressing challenges of prolonged scans and patient discomfort.This paper presents a new method for compressing and reconstructing MRI images using k-space gradients.A hybrid under-sampling approach allocates 80% of measurements to random sampling and 20% to deterministic sampling near the k-space center.Additionally, it explores the impact of reducing kx samples by 15%, 25%, and 50% on image quality.Reconstruction uses a nonlinear conjugate gradient method, with image quality assessed via a similarity index Q.Results show the proposed CS approach effectively compresses MRI data while preserving essential image quality, optimizing protocols and reducing scan times.
DOI: 10.15439/2024r58
Authors: Duc-Tan Tran, Quang Huy Pham, Thi Phuong Hanh Nguyen, Trinh Thi Thu Huong
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4410513347