Preoperative assessment with FDG Pet CT scan.
Nuclear Medicine, Tizi Ouzou, Algeria
Artificial intelligence (AI) has been explored as a potential solution for breast cancer detection. However, most AI systems have been trained specifically for this purpose. While these systems show promise in detecting breast cancer, there is growing recognition for the importance of quality checks before interpretation.
Until now, the focus has primarily been on training AI to detect breast cancer. However, some vendors are beginning to realize the significance of evaluating the quality of mammograms prior to any interpretation. This is crucial as poor image quality can lead to inaccurate readings and potential misdiagnosis.
In the near future, we are likely to see new algorithms being developed and trained specifically for evaluating mammogram quality. These algorithms will help ensure that only high-quality images are used for interpretation, thereby increasing the accuracy and reliability of AI systems in breast cancer detection.
While AI has shown great potential in breast cancer detection, it is important to recognize the need for quality checks before interpretation. In the coming year, we can expect to see new algorithms being developed and trained for evaluating mammogram quality. This will help improve the accuracy and reliability of AI systems in detecting breast cancer.
Jean-Philippe SPANO
Chairman of Oncology department , University hospital Pitié-Salpétrière, Paris, France
Fréderique PENAULT LORCA
Chairwoman of the Pathology department, University Hospital, Clermont Ferrand, France
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