#TITLE_ALTERNATIVE#

• Main Author: MURTIAAFI IRIANTO (NIM : 10213007), RIZKY
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/30621
• Institution: Institut Teknologi Bandung

<p align="justify">Within the development of CT, the quality of the image is better but the dose is also greater than before. While the results of image quality of CT are very important to determine the next medical step. Therefore, the improvement of image quality is important to do, so that the doses given to the patient can be minimized and the quality of the image can be as good as possible. In this research, the researcher aimed to reduce noise by mean filter method and median filter method and also to enhance contrast in CT image with histogram equalization method and contrast stretching method. And lastly, merging methods to reduce noise and enhance contrast and then compared with the original image which aims to find which method produces good image quality. But before that, researcher have added noise in the original image using Pyhton programming language to see the difference after and before in both noise reduction, contrast enhancement and combined methods. The original image used is a 512x512 pixel lung cancer image and for contrast enhancement using image in 430x430 and 390x390 pixel 8 bit. By using Python programming language, each image is done with noise reduction by mean filter method and median filter. While to enhance contrast used histogram equalization and contrast stretching method. To determine image quality, image needs to be quantized using PSNR, MSE, and CNR with FIJI. The results for smoothing method and contrast enhancement are median filter and contrast stretching which produce good quality image. And for the combination of both methods, the result in good image quality is the median filter-contrast stretching and also the sequence in the combination of the method can produce different results.<p align="justify">