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Browsing Enstitüler by Author "Aksebzeci, Bekir Hakan"

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    Master Thesis
    Meme Kanseri Histopatoloji Görüntülerinde Evrişimsel Sinir Ağları Kullanarak Tümör Tespiti
    (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024) Şahbaz, Zeki; Aksebzeci, Bekir Hakan; AGÜ, Fen Bilimleri Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalı; 01. Abdullah Gül University
    Breast cancer is one of the most common cancer types among women worldwide. Early detection significantly increases the chances of survival and effective treatment, making advancements in diagnostic methodologies crucial. This study aims to improve the detection of tumor cells in breast cancer histopathology images using deep learning and image processing techniques. Significant modifications have been made to the hyperparameters, including the tumor bounding box size, batch size, optimization algorithms, learning rate, and weight decay. These changes focus on determining the best parameters of the Faster R-CNN model. A comprehensive analysis of different parameters was conducted using the Breast Cancer Histopathological Annotation and Diagnosis (BreCaHAD) dataset. The analysis identified the best settings for model performance, shows by improvements in precision, recall, and F-score. Our research contributes to the field of medical image analysis by identifying critical factors that affect the accuracy of tumor detection, contributing to the development of more accurate diagnostic tools.