MRD File Processing for MRI Results: MATLAB Application and Opening Program

In magnetic resonance imaging (MRI) technology, MRD files are raw data files generated by MRI systems, containing crucial K-space data. K-space data represents unprocessed frequency-domain signals that can be transformed into visual MRI images through Fourier transform operations.

Processing MRD files with MATLAB typically involves the following key steps:

File Reading The initial step requires reading MRD files through MATLAB and parsing their binary data structure. MRD files typically contain complex header information and K-space data blocks, necessitating careful attention to data structure parsing methods to ensure accurate extraction of K-space data. MATLAB's fread function can be employed with appropriate data type specifications to handle the binary format efficiently.

K-space Data Processing K-space represents the frequency-domain expression of MRI signals, usually stored in complex number format. In MATLAB, developers can manipulate K-space data layout through operations like data reorganization or noise reduction processing to improve image reconstruction quality. Common techniques include using fftshift to center the K-space data and applying filters for noise reduction before reconstruction.

Fourier Transform Image Reconstruction Applying two-dimensional or three-dimensional inverse Fourier transform (IFFT) to K-space data generates magnetic resonance images. MATLAB provides efficient FFT functions (ifft2 for 2D, ifftn for n-dimensional) that enable rapid conversion. The reconstructed images may require additional phase correction or amplitude adjustment using functions like abs for magnitude extraction and angle for phase handling to ensure clear visual representation.

Multi-layer Image Observation For MRD files containing multi-slice scan data (such as 3D MRI), MATLAB enables layer-by-layer display through slicing techniques or 3D reconstruction for立体 observation. Users can optimize image contrast by adjusting window width and level settings using imcontrast tools, facilitating medical analysis. The slice function allows interactive browsing through image stacks, while volumeViewer provides comprehensive 3D visualization capabilities.

Through this workflow, MATLAB not only assists researchers in efficiently parsing MRD files but also offers flexible image post-processing functionalities, providing substantial support for medical image analysis applications.