Lunit (KRX:328130.KQ), a leading global provider of AI-powered cancer diagnostic solutions,  announced its participation in the Conference on Computer Vision and Pattern Recognition 2023 (CVPR 2023) to be held at the Vancouver Convention Center from June 18th to 22nd.

CVPR is renowned as one of the premier conferences in the field of computer vision and pattern recognition, boasting an impressive impact with an h-index of 470^[1]. Lunit's presence at this prestigious event marks a significant milestone as it showcases its pioneering studies in computer vision technology for medical AI and pathology.

Lunit will present two full papers that highlight the company's commitment to revolutionizing cancer diagnostics and therapeutics through cutting-edge AI methodologies. The first paper introduces the novel OCELOT dataset, a breakthrough development containing overlapping cell and tissue annotations on histopathology images. By harnessing this dataset and employing a groundbreaking method, Lunit significantly enhances the accuracy of cell detection, taking a vital stride towards developing more precise and advanced AI systems.

In the second study, Lunit unveils the potential of self-supervised learning (SSL), an innovative approach that eliminates the need for experts to manually label cells in pathology images. By leveraging this technique, Lunit conducted the largest-ever study of its kind on pathology images, utilizing a staggering 33 million image patches that required no manual labeling. The results of this study demonstrate the efficacy of self-supervised learning and showcase Lunit's distinctive enhancements that further optimize its application in pathology.

"We are incredibly excited to participate in CVPR 2023 and share our groundbreaking research in computer vision for medical AI," said Brandon Suh, CEO of Lunit. "By leveraging our expertise and cutting-edge technologies, we are on a mission to revolutionize digital pathology, empowering clinicians with more accurate and efficient tools for improved patient outcomes."

Based on the newly released OCELOT dataset, Lunit is hosting the OCELOT 2023 Challenge at the 2023 Medical Image Computing and Computer Assisted Intervention (MICCAI 2023). The challenge aims to foster research of cell-tissue relationships to improve cell detection methodologies.