An Efficient Approach for Converting 2D Medical Images Into Non Immersive VR Model - Mohamed Sathik, M; Farzana, A; Shajun Nisha, S (International Journal of Computer Sciences and Engineering, 2021)
The primary objective of this paper is to find out an efficient approach for converting 2D medical images into a desktop level VR model. The target is achieved in three stages: segmentation, 2D to 3D reconstruction, and 3D to VR modeling. Segmentation is the process of partitioning the digital image into sub parts or meaningful segments which help in segregating the cognitive information in the region of interest. Several segmentation algorithms are used to segment the input image. Best segmentation techniques are preferred for 3D reconstruction. Two types of 3d reconstruction techniques are used in formulating a 3D model. The AMILab 3.2.0 is used to provide non immersive visualization. Quantitative metrics such as Accuracy, Sensitivity, Specificity, Precision, F Score, Border Error, Jaccard Distance, Volumetric Overlap Error, Relative Volume Difference, Average Symmetric surface Distance and Maximum Symmetric surface Distance are used to evaluate the performance. Constructed VR model helps students in learning human anatomy efficiently.