Quantitative MRI post-processing algorithm and visualization research based on moisture status detection of winter jujube
Year: 2024
Type: article
Abstract: Quantitative Magnetic Resonance Imaging (qMRI) offers precise measurements of the relaxation characteristics of microstructures, representing a cutting-edge method in non-destructive fruit analysis. This study aims to visualize information on changes in moisture status and distribution at the subcellular level of winter jujube. The 0.5 T nuclear magnetic imaging equipment was utilized to rapidly, non-invasively, and accurately capture the internal relaxation status of the sample with multiple-echo-imaging. By examining the signal and noise data, a simulated dataset was developed to tackle the optimization challenge of estimating parameters for the discrete relaxation model from the multiple-echo-imaging data, especially under conditions of low signal-to-noise ratio (SNR) and in the context of heteroscedastic noise. An optimal weighting factor and the T 2 NR truncation model have been identified to establish an effective experimental inversion strategy. Subsequently, multiple-echo-imaging can rapidly and stably yielded voxel-level maps under conditions of low signal-to-noise ratio. Utilizing this experimental approach, data from winter jujube was collected and analyzed, facilitating an exploration of water activity (T 2 mapping) and associated water content (A 2 mapping). Through analyzing winter jujube fruits across two maturity stages, this study elucidates the role of precise quantification and voxel-wise visualization in moisture status detection. The methodology presents an innovative approach for assessing internal moisture distribution in fruits.
Source: Heliyon
Authors: Yanan Li, Yijin Wang, Guifa Teng, Jingfa Yao, Peng Luan
Institution: Hebei Agricultural University
Language: English
Subfield: Nuclear and High Energy Physics
Field: Physics and Astronomy
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $2,100
Funders: National Natural Science Foundation of China, National Aerospace Science Foundation of China, Yunnan Provincial Department of Education Science Research Fund Project, Curtin Health Innovation Research Institute, Curtin University, Special Project for Research and Development in Key areas of Guangdong Province
OpenAlex ID: W4401626489