Effect of Different Parameter Values for Pre-processing of Using Mammography Images
Breast cancer is one of the most common types of cancer in women. To make a fast diagnosis, mammography images should have high contrast. Computer-assisted diagnosis (CAD) models are computer systems that help diagnose lesioned areas on medical images. The aim of this study is to examine the contrib...
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Çanakkale Onsekiz Mart University
2023-06-01
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| Series: | Journal of Advanced Research in Natural and Applied Sciences |
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| Online Access: | https://dergipark.org.tr/en/download/article-file/2750938 |
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| author | Hanife Avcı Jale Karakaya |
| author_facet | Hanife Avcı Jale Karakaya |
| author_sort | Hanife Avcı |
| collection | DOAJ |
| description | Breast cancer is one of the most common types of cancer in women. To make a fast diagnosis, mammography images should have high contrast. Computer-assisted diagnosis (CAD) models are computer systems that help diagnose lesioned areas on medical images. The aim of this study is to examine the contribu-tion of the changes in parameter values of various pre-processing methods used to increase the visibility of mammography images and reduce the noise in the images, to the classification performance. In this study, the mini-MIAS database were used. Gaussian filter, Contrast Limited Adaptive Histogram Equalization and Fast local Laplacian filtering methods were applied as pre-processing method. In this study, two different parameter values were applied for two different image processing methods (Ⅰ. Parameter values are Gauss filter 𝜎=3, Laplacian filter 𝜎=0.6 and 𝛼=0.6; Ⅱ. Parameter values are Gauss filter 𝜎=1, Laplacian filter 𝜎=2 and 𝛼=2). In the normal-abnormal tissue classification, higher accuracy and area under the curve were obtained in the 2nd parameter values in all classification methods. As a result, it has been acquired that different parameter values of the pre-processing methods used to improve mammography images can change the success of the classification methods. |
| format | Article |
| id | doaj-art-8a4604b7869e4e5889c04206fbbeeddc |
| institution | Kabale University |
| issn | 2757-5195 |
| language | English |
| publishDate | 2023-06-01 |
| publisher | Çanakkale Onsekiz Mart University |
| record_format | Article |
| series | Journal of Advanced Research in Natural and Applied Sciences |
| spelling | doaj-art-8a4604b7869e4e5889c04206fbbeeddc2025-02-05T17:57:35ZengÇanakkale Onsekiz Mart UniversityJournal of Advanced Research in Natural and Applied Sciences2757-51952023-06-019234535410.28979/jarnas.1199343453Effect of Different Parameter Values for Pre-processing of Using Mammography ImagesHanife Avcı0https://orcid.org/0000-0002-1405-9754Jale Karakaya1https://orcid.org/0000-0002-7222-7875HACETTEPE UNIVERSITYHACETTEPE ÜNİVERSİTESİ, TIP FAKÜLTESİBreast cancer is one of the most common types of cancer in women. To make a fast diagnosis, mammography images should have high contrast. Computer-assisted diagnosis (CAD) models are computer systems that help diagnose lesioned areas on medical images. The aim of this study is to examine the contribu-tion of the changes in parameter values of various pre-processing methods used to increase the visibility of mammography images and reduce the noise in the images, to the classification performance. In this study, the mini-MIAS database were used. Gaussian filter, Contrast Limited Adaptive Histogram Equalization and Fast local Laplacian filtering methods were applied as pre-processing method. In this study, two different parameter values were applied for two different image processing methods (Ⅰ. Parameter values are Gauss filter 𝜎=3, Laplacian filter 𝜎=0.6 and 𝛼=0.6; Ⅱ. Parameter values are Gauss filter 𝜎=1, Laplacian filter 𝜎=2 and 𝛼=2). In the normal-abnormal tissue classification, higher accuracy and area under the curve were obtained in the 2nd parameter values in all classification methods. As a result, it has been acquired that different parameter values of the pre-processing methods used to improve mammography images can change the success of the classification methods.https://dergipark.org.tr/en/download/article-file/2750938computer-assistedimage enhancementimage processingmachine learningclassification |
| spellingShingle | Hanife Avcı Jale Karakaya Effect of Different Parameter Values for Pre-processing of Using Mammography Images Journal of Advanced Research in Natural and Applied Sciences computer-assisted image enhancement image processing machine learning classification |
| title | Effect of Different Parameter Values for Pre-processing of Using Mammography Images |
| title_full | Effect of Different Parameter Values for Pre-processing of Using Mammography Images |
| title_fullStr | Effect of Different Parameter Values for Pre-processing of Using Mammography Images |
| title_full_unstemmed | Effect of Different Parameter Values for Pre-processing of Using Mammography Images |
| title_short | Effect of Different Parameter Values for Pre-processing of Using Mammography Images |
| title_sort | effect of different parameter values for pre processing of using mammography images |
| topic | computer-assisted image enhancement image processing machine learning classification |
| url | https://dergipark.org.tr/en/download/article-file/2750938 |
| work_keys_str_mv | AT hanifeavcı effectofdifferentparametervaluesforpreprocessingofusingmammographyimages AT jalekarakaya effectofdifferentparametervaluesforpreprocessingofusingmammographyimages |