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Can breast cancer screening be improved with artificial intelligence?

We investigate the possibilities to use artificial intelligence to improve breast cancer screening with either standard mammography (2D) or breast tomosynthesis (3D mammography).

Today mammography is used for breast cancer screening. In order to detect as many cancers as possible, each image is read by two specialised breast radiologists. Breast tomosynthesis can find more cancers, but takes about twice the time to read. This is an obstacle to replace mammography with breast tomosynthesis in screening, not least because there is a shortage of breast radiologists.


We study if a computer with artificial intelligence could help in reading the images, so it can both be faster and at the same time find more cancers. Maybe artificial intelligence can identify suspicious areas, which the radiologists should study more thoroughly in order to detect more cancers. Another alternative could be if artificial intelligence can make a preselection and make it possible to focus the radiologists’ time on the women with the highest risk of cancer. This could make it be possible to screen all women with breast tomosynthesis, but keep the total reading time at the same level as when using mammography. More cancers could be detected earlier, hopefully at a curable stage, with the same resources as mammography screening.

Radiological image of a breast


Main supervisor: Sophia Zackrisson

Co-supervisors: Anders Tingberg, Magnus Dustler