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. 2024 Jun 17:55:110633.
doi: 10.1016/j.dib.2024.110633. eCollection 2024 Aug.

Mammogram mastery: A robust dataset for breast cancer detection and medical education

Karzan Barzan Aqdar  1 , Rawand Kawa Mustafa  1 , Zhiyar Hamid Abdulqadir  1 , Peshraw Ahmed Abdalla  2 , Abdalbasit Mohamad Qadir  1 , Alla Abdulqader Shali  3 , Nariman Muhamad Aziz  4   5
Affiliations

Mammogram mastery: A robust dataset for breast cancer detection and medical education

Karzan Barzan Aqdar et al. Data Brief. .

Abstract

This data article presents a comprehensive dataset comprising breast cancer images collected from patients, encompassing two distinct sets: one from individuals diagnosed with breast cancer and another from those without the condition. Expert physicians carefully select, verify, and categorize the dataset to guarantee its quality and dependability for use in research and teaching. The dataset, which originates from Sulaymaniyah, Iraq, provides a distinctive viewpoint on the frequency and features of breast cancer in the area. This dataset offers a wealth of information for developing and testing deep learning algorithms for identifying breast cancer, with 745 original images and 9,685 augmented images. The addition of augmented X-rays to the dataset increases its adaptability for algorithm development and instructional projects. This dataset holds immense potential for advancing medical research, aiding in the development of innovative diagnostic tools, and fostering educational opportunities for medical students interested in breast cancer detection and diagnosis.

Keywords: Artificial intelligence; Breast cancer; Deep learning; Image augmentation; Machine learning; Mammography.

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Figures

Fig. 1
Fig. 1
Samples from the original dataset.
Fig. 2
Fig. 2
Visual representation of augmented images generated using various techniques.
Fig. 3
Fig. 3
Visual abstract.
See this image and copyright information in PMC

References

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