Studi Perbandingan Metode Histogram Equalization Dan Metode Contrast Limited Adaptive Histogram Equalization Padacitra CT Scan Patah Tulang
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Institusion
Institut Teknologi Telkom Purwokerto
Author
Almasy, Syahidah
Subject
T Technology (General)
Datestamp
2022-04-11 07:43:59
Abstract :
Fractures are accidents that are often found in everyday life. In fact, almost everyone in the world has experienced a fracture at least once in their life. The causes of fractures such as accidents, cracks, osteoporosis, and others. Fractures can be identified by direct human visuals, x-rays, CT scans, or MRIs. In this study, a comparative analysis of the histogram equalization (HE) method and the contrast limited adaptive histogram equalization (CLAHE) method will be carried out on CT Scan images of normal bones and CT Scan images of fractured bones, as well as classifying CT Scan images of normal bones and CT Scan images of fractures inparameter pixel value generated by the image using the k-nearest neighbor (KNN) method to find out which method is better. The writer got the data from MURA dataset. With this study, it can be seen that CT Scan image processing can be seen more clearly when using the histogram equalization method compared to the contrast limited adaptive histogram equalization method. The calculation of accuracy using the k-nearest neighbor generated by the histogram equalization has an accuracy rate above 50% or >50% from 10 tests using a dataset of 1400. Keywords: Fractures, CT Scan, Histogram Equalization, Contrast Limited Adaptive Histogram Equalization, Image Processing, K-Nearest Neighbor.
Fractures are accidents that are often found in everyday life. In fact, almost everyone in the world has experienced a fracture at least once in their life. The causes of fractures such as accidents, cracks, osteoporosis, and others. Fractures can be identified by direct human visuals, x-rays, CT scans, or MRIs. In this study, a comparative analysis of the histogram equalization (HE) method and the contrast limited adaptive histogram equalization (CLAHE) method will be carried out on CT Scan images of normal bones and CT Scan images of fractured bones, as well as classifying CT Scan images of normal bones and CT Scan images of fractures inparameter pixel value generated by the image using the k-nearest neighbor (KNN) method to find out which method is better. The writer got the data from MURA dataset. With this study, it can be seen that CT Scan image processing can be seen more clearly when using the histogram equalization method compared to the contrast limited adaptive histogram equalization method. The calculation of accuracy using the k-nearest neighbor generated by the histogram equalization has an accuracy rate above 50% or >50% from 10 tests using a dataset of 1400. Keywords: Fractures, CT Scan, Histogram Equalization, Contrast Limited Adaptive Histogram Equalization, Image Processing, K-Nearest Neighbor.
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