You can anonymize multiple files in terms of various criteria, such as patient name, study date, series time, content time, institution name and address, station name, study description, patient’s weight, and operator’s name. size, pixel spacing, type, patient position), show a histogram, as well as display a list with DICOM tags. name, ID, birthdate, series) and image (e.g. MIView is able to retrieve information about the patient (e.g. However, it eats up CPU and memory so the overall performance of the computer may be hampered. The tool provides very good image quality. You can adjust the zoom level and viewing plane, rotate objects to different angles, and choose between several viewing modes, namely Normal, Orthogonal, Multislice, Maximum Intensity Projection, Surface Shaded Display, and Volume Rendering. MIView provides a coherent feature structure where you can add files in the working environment using the built-in browse button (you cannot rely on the drag-and-drop support). You can open only the selected file or all items in the folder with the same extension, automatically detect the file format, and set up DICOM mosaic options (size and number of slices).
MIView works with various file formats, namely DCM, ACR, PAP, IMG, HDR, GIF, TIFF, PNG, BMP, and JPEG. It is Java-based so you need to previously deploy the working environment on your computer. Medical Image Viewer (MIView) is a lightweight medical image viewer based on OpenGL that comes with support for DICOM anonymizer and file conversion tasks.
0 kommentar(er)
