AI in Digital Pathology

What benefits does AI offer digital pathologists? How can it revolutionize the field and what are its biggest challenges?

Pathology is a sub-field of medical science that aims to research and develop new and efficient drugs and treatment procedures. The advances in machine learning and artificial intelligence affected this field, creating a new division called digital pathology.

Under digital pathology, microscopic images of tissue samples are transferred to a computer, where they are analyzed using advanced image processing techniques and computer vision.

Digitization of medical imagery and diagnosis opens up avenues for artificial intelligence in pathology. Pathologists can use machine learning models to conduct enhanced analysis and improve result accuracy. Moreover, AI in pathology provides second opinions to practitioners, further aiding their day-to-day work.

Many applications for AI in pathology aid clinical analysis by providing faster and more accurate diagnoses.

Improved cancer diagnosis and treatment

Developing efficient cancer treatment has been a challenge for medical practitioners. Although conventional biopsy results are highly accurate, finalizing the results requires a significant amount of time.

Artificial intelligence systems can gather, and process required information within minutes and produce cancer outcomes with an accurate diagnosis. Researchers and pathologists have developed several AI models that demonstrate the capabilities of machine learning algorithms for cancer and tumor detection.

Computational Pathology Group (CPG), a research group from the Department of Pathology at Radboud University Medical Center, has developed and deployed several medical image analysis applications. Their recent project combines digitized whole-slide prostate cancer images with deep learning techniques. The project aims to detect novel quantitative biomarkers to prevent unnecessary surgeries.

Another of CPG's publications demonstrates the use of existing datasets to predict new targets. They obtained state-of-the-art performance on colon and head-and-neck cancer metastasis tasks using high-quality datasets and networks from metastatic breast cancer patients.

Many international biotechnology firms use artificial intelligence to enhance digital pathology procedures.