Transforming Breast Cancer Diagnosis with Artificial Intelligence

Breast cancer is the most common cancer and second leading cause of cancer-related death worldwide. According to the World Health Organization (WHO), a total of 2.3 million women were diagnosed with breast cancers with about 685,000 mortalities globally. The high incidence and mortality rates of breast cancer, as well as the high cost of treatment make it one of the most important global public health problems. Diagnosis of breast cancer during the early stages of disease has been positively linked to a decrease in the mortality and morbidity of the illness. AI-powered digital pathology has the potential to automate all kinds of work involved in tumor pathology, including tumor diagnosis, subtyping, grading, staging, and prognostic prediction.

Crosscope™ is building AI powered digital pathology platform that enable pathologists with efficient workflows and increased productivity alongside improved diagnostic accuracy. Crosscope’s OrionAI™ Breast module is a deep-learning-based breast cancer grading approach which automatically classifies the biopsy slide as cancer or normal and then identifies tumor regions with heatmap overlays for further examination by the pathologist. The pathologist’s burden is reduced by automatically detecting diagnostically important regions-of-interest (ROIs), while also ensuring that no crucial region is missed. OrionAI™ aims to automate pathologists’ time-consuming and error-prone pre-diagnostic tasks, allowing them to make efficient and more accurate diagnoses.

Learn more about Crosscope’s technology and OrionAI™ in the whitepaper below.

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