VinBrainer's outstanding paper accepted at ACCV 2024

VinBrain is proud to announce that the research paper titled “A Multi-Phase Multi-Graph Approach for Focal Liver Lesion Classification on CT Scans,” authored by AI - Image Processing Team Lead (Applied Science Division) Tran Bao Sam, has been accepted for presentation at the prestigious 17th Asian Conference on Computer Vision - ACCV 2024 - A premier forum for researchers, developers, and practitioners to present and discuss new problems, solutions, and technologies in computer vision, machine learning, and related areas in artificial intelligence.

At the conference, Sam will represent VinBrain to introduce a novel multi-phase multi-graph (MPMG) approach to improve liver tumor classification using contrast-enhanced computed tomography (CECT) scans.

Most existing approaches focus only on analyzing individual lesions in isolation, without considering the potential influence of neighboring lesions, this new approach will provide the potential to standardize diagnostic criteria, reduce human error, and improve overall diagnostic accuracy. This is also the method being applied to develop the pioneering product for liver cancer diagnosis and treatment, hashtag#DrAid™ CT Liver Cancer.

Being in the top 32% of accepted papers from a pool of 839 submissions worldwide and having our research presented at the prestigious ACCV 2024 is a huge honor for our team at VinBrain. This, combined with our many publications in leading scientific journals, shows that we're a place where brilliant minds come together to create innovative solutions for healthcare around the world.