Medical Image Data Conversion to Design Anatomical 3D Models for Creative Medical Applications

Abstract

        This academic paper reports a practical guide to creating an anatomical 3D design using medical image data conversion techniques and examines the creative purposes of using anatomical 3D models in the medical field. Anatomical 3D models are regularly used in clinical training, diagnoses, and surgical planning for physicians. The creation of anatomical 3D models has required accuracy of size, scale, and proportion of anatomical data. Hence, the technology in medical imaging, such as CT scan and MRI, is used to capture precise anatomical data from patients. However, the anatomical images dataset from CT Scan and MRI are only two-dimensional and require further processing to convert the file to a 3D model. Two different medical image file formats are generally used in healthcare, namely PACS and DICOM. This paper has demonstrated the features of the DICOM file format that contained better references data, such as slicing thickness, spacing between slices, and converting image resolution to a 3D Model. The methods to convert DICOM to STL file format also require specific techniques to handle the automatically generated function from open-source programs with lower image quality. The author described the improvement techniques by using Materialize Mimics software to adjust parameters and selected tissue surfaces before conversion to Stereolithography (STL) file. With the STL file format, physicians can edit and design the 3D models to achieve objectives and use anatomical 3D models for other creative purposes. 

 Keywords: Medical image data, 3D Design, anatomical model, 3D printing, Computer-Aided Design, Rapid-Prototyping, CT Scan, PACS, DICOM, STL