Medical SpecialtyOpen Access

Özellik piramitleri ve CNN algoritması kullanarak röntgen görüntülerinde meme kanseri tespiti

2022
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Advisor: Assist. Prof. Dr. Ayça Kurnaz Türkben

Abstract (EN)

ABSTRACT-Breast cancer is the most common type of cancer worldwide. Among women, it is the most recurrent type and the second leading cause of death in the Americas, in addition to accounting for about 25% of new cases each year Early detection of breast cancer is essential to increase the chances of treatment and cure effectively, which reduces the mortality rate caused by this disease Mammography is the most common test for detecting breast cancer. The methodology used during this work is inspired by the CNN methodology. The latter emphasizes communication and collaboration between development teams and the client. The most important point of the Agile methodology is communication. During the realization of this project, during this, two points are addressed. First of all, the work carried out during the week is presented and the difficulties encountered are discussed if necessary. Once this part is completed, the modifications to be made and the additions desired for the following week are defined. KEYWORDS: AI, CAD, CNN, X-RAY

Author

Dr. Ahmed Abdulkarım Kado Al Tahan

How to Cite

Ahmed Abdulkarım Kado Al Tahan (Medical Specialty Thesis). Özellik piramitleri ve CNN algoritması kullanarak röntgen görüntülerinde meme kanseri tespiti, 2022, Altınbaş University.

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