Image Processing: Manual Segmentation on 3D Femur Bone Model

Image processing popularly reconstructs the original image to become the intended image that reveals certain information. In the medical field, a technique of image processing, particularly segmentation, is a fundamental step for further analysis. This study aims to segment the femur bone in a three-dimensional (3D) model from the whole image area of the lower extremity for any other medical purpose, such as implant or surgery planning. This study's segmentation is building a specific algorithm using Matlab. This technique is considered to eliminate the drawbacks of automated software in the segmentation process, such as DICOM viewer and analyzing software with inconsistent accuracy and purchase at high cost. Results from this study show that the segmented femur model has more prolonged, about 30%, than the original image. Although the measurement also finds significant differences between automatic and manual segmentation, this trial significantly increases knowledge of the possibility of using manual segmentation to solve problems while using the DICOM viewer software.