Özet:

This article presents a literature review on image preprocessing methods, focusing on the use of tomosynthesis images in deep learning studies. Tomosynthesis is an advanced medical imaging technique that provides 3-dimensional, cross-sectional scanning of breast tissue. The images obtained with this technique can be higher dimensional and noisier than 2D mammograms. Therefore, preprocessing is required to make these images suitable for deep learning models. This literature review addresses the different preprocessing methods used in tomosynthesis images. First of all, an introduction will be made about the properties of Tomosynthesis images and deep learning methods. Then, information about the techniques such as filtering, normalization, segmentation and augmentation, which are among the preprocessing methods used, will be given from the literature search. In addition, examples where these methods are used together will also be examined. In conclusion, with this article, it is aimed to present a useful Turkish resource to researchers who want to do deep learning studies on Tomosynthesis images. The research shows that the right choice of image preprocessing methods can significantly improve the performance of deep learning models.

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