Computer Vision News 24 AI for Medical Imaging Breast cancer is the second most common cancer in women (skin cancer is the first) and a significant challenge to healthcare systems globally. The risk of developing breast cancer increases with age and is influenced by factors such as someone’s genetic makeup and family history. Like other serious health conditions and diseases, early detection of breast cancer is essential to improving survival rates, and routine breast screening is a critical part of this. Women over 40 are recommended to have a mammography examination once a year. In addition, MRI and ultrasound exams may be offered to high-risk people with a family history of breast cancer or those who are carriers of the BRCA gene. However, traditional screening modalities can expose patients to unintended risks, like harmful radiation from mammography, and create unsustainable workloads for radiologists, raising the possibility that they will be tired and make mistakes. Incorporating artificial intelligence (AI) can help solve these challenges and optimize breast cancer screening efficacy, accuracy, and efficiency, ultimately driving progress in the fight against this disease. Mammography involves the breast being pressed between two surfaces and a 2D X-ray image or a 3D tomography scan via tomosynthesis being captured. A radiologist then examines these scans to identify suspicious lesions or areas requiring further investigation. In performing this scan, there is a delicate balance between radiation dosage and image quality. With the help of AI, radiation exposure can be reduced by training neural networks to reconstruct highquality images from lower-quality ones. Classic computer vision techniques and more advanced deep learning methods can help detect and segment suspicious landmarks, relieving the pressure on radiologists and increasing precision. Breast MRI, though highly effective, has long examination times due to the acquisition of multiple sequences and the person’s breathing, which causes movement that must be taken into account. Deep learning techniques can register each sequence to a predefined baseline, Enhancing Breast Cancer Screening with AI Breast MRI - MIP with subtraction showing enhanced procedure in left breast
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