Ripening Study Based on Multi-Structural Inversion of Cherry Tomato qMRI.

This study introduces a non-destructive, quantitative method using low-field MRI to assess moisture mobility and content distribution in cherry tomatoes. This study developed an advanced 3D non-local mean denoising model to enhance tissue feature analysis and applied an optimized TransUNet model for structural segmentation, obtaining multi-echo data from six tissue types. The structural T2 relaxation inversion was refined by integrating an ACS-CIPSO algorithm.

Quantitative MRI post-processing algorithm and visualization research based on moisture status detection of winter jujube.

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.

Three-dimensional reconstruction and phenotype measurement of maize seedlings based on multi-view image sequences.

As an important method for crop phenotype quantification, three-dimensional (3D) reconstruction is of critical importance for exploring the phenotypic characteristics of crops. In this study, maize seedlings were subjected to 3D reconstruction based on the imaging technology, and their phenotypic characters were analyzed. In the first stage, a multi-view image sequence was acquired an RGB camera and video frame extraction method, followed by 3D reconstruction of maize based on structure from motion algorithm.