The goal of this study is to assess the efficiency of Artificial Bee Colony (ABC) algorithm in finding the optimal solution of curve fitting problem specifically for medical images. Data of Computed Tomography (CT) images from two different patients were collected. The procedure of curve fitting for medical images include conversion of Digital and Communications in Medicine (DICOM) images to binary images, boundary and corner point detection, parameterization, and curve reconstruction by using ABC algorithm. Then, Sum Square Error (SSE) was used to calculate the distance of the fitted Cubic Bezier curve with the boundary of the original images. Based on the calculation and parameter tuning that had been done, the smallest error of both skulls is57.5754and28.8628, respectively. The finding of this study illustrated that the proposed method had efficiently produced fitted Bezier curve that resemble the original medical images. In addition, the used of Douglas Peucker algorithm helps to improve the performance of the proposed method since computational time can be minimized. This study had shown that the proposed method can be used as an alternative method in order to reconstruct or redesigned the medical images since it produces a small error. For future work, we are planning to explore and applied the ABC algorithm to reconstruct the missing part of the skull since it can reduce the time taken to produce the skull implant as well as reducing the cost of producing it.

There are four main processes involved during the reconstruction of bitmap images, which include boundary detection, corner points detection, parameterization and curve fitting. This paper presents the use of Artificial Bee Colony (ABC) algorithm during the process of parameterization and cubic Bézier curve was used for the reconstruction of generic shapes by using Least Square method. Since the purpose of this study is to minimize the distance between boundary of the original image and parametric curve, Sum Square Error (SSE) has been used to calculate the error given by these two curves. The results obtained by using ABC algorithm will be compared with the results obtained when using chord length method during the parameterization process. Note that, for the comparison purpose, the same images have been used and the procedure remains the same except for parameterization process. The finding of this study illustrates that the proposed method has successfully generated fitted cubic Bézier curve that resembles the boundary of original images and enhances its performance since it produces a small error as compared to the result obtained by using chord length parameterization method.

In the article titled “Reconstruction of Medical Images Using Artificial Bee Colony Algorithm” [1], the Acknowledgments section should be corrected as follows.