KLASIFIKASI CITRA MAMMOGRAM KANKER PAYUDARA MENGGUNAKAN METODE CNN
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
OCSANDRIANTO, FAJAR
Kuswardani, Dwina
Agtriadi, Herman Bedi
Kuswardani, Dwina
Agtriadi, Herman Bedi
Subject
Teknik Informatika
Datestamp
2023-05-31 07:44:57
Abstract :
Breast cancer is a condition where the growth of cells is uncontrolled and abnormal in the breast tissue. Breast cancer usually attacks the milk tissue and can spread to the surrounding area. One of the checks for breast cancer is by examining a doctor using x-rays which produce mammogram images that are useful for seeing inside the breast whether there is breast cancer that cannot be seen with the naked eye. However, mammogram results that are not always good can affect doctors in making a diagnosis. This is the aim of the research conducted which implements the Convolutional Neural Network method for the system that is created. Which has the aim of being a comparison between visual observations and computational observations in an effort to increase accuracy in making a diagnosis in the classification of mammogram images that detect between benign and malignant. In this study kernel sharpen (Matrix 3x3) was also used to help sharpen the image. Researchers used a dataset of 641 in conducting this study. To get the results of the classification test made using the Confusion Matrix. And the results are based on the process by taking 20 data samples that were tested on the system resulting in an accuracy of 75%.
Breast cancer is a condition where the growth of cells is uncontrolled and abnormal in the breast tissue. Breast cancer usually attacks the milk tissue and can spread to the surrounding area. One of the checks for breast cancer is by examining a doctor using x-rays which produce mammogram images that are useful for seeing inside the breast whether there is breast cancer that cannot be seen with the naked eye. However, mammogram results that are not always good can affect doctors in making a diagnosis. This is the aim of the research conducted which implements the Convolutional Neural Network method for the system that is created. Which has the aim of being a comparison between visual observations and computational observations in an effort to increase accuracy in making a diagnosis in the classification of mammogram images that detect between benign and malignant. In this study kernel sharpen (Matrix 3x3) was also used to help sharpen the image. Researchers used a dataset of 641 in conducting this study. To get the results of the classification test made using the Confusion Matrix. And the results are based on the process by taking 20 data samples that were tested on the system resulting in an accuracy of 75%.
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