Fujifilm and IU School of Medicine to Study AI in Diagnostic Imaging
By Medimaging International staff writers
12 Sep 2018
Fujifilm Corporation (Tokyo, Japan) has entered into a joint research agreement with Indiana University School of Medicine (Indianapolis, IN, USA) to develop the application of artificial intelligence (AI) in medical imaging diagnostic support systems.
Going forward, as clinical information is increasingly viewed in the context of big data, AI technology will be applied to develop products that meet the different and challenging needs of the healthcare industry. For instance, recent technological advancements in diagnostic imaging system capabilities, such as multi-slice CT, have created the need for an efficient solution to read and interpret the increased number of images being generated. The application of AI technology to support physicians by detecting suspicious lesions in images, comparing results with prior studies and the implementation of semi-automated reporting is expected to significantly increase the efficiency of diagnostic medical imaging in patient care.
Fujifilm is using AI technology to develop image diagnosis support systems, which will support the overall diagnostic workflow of physicians. In addition to undertaking various in-house development projects, Fujifilm is also entering into a partnership with leading AI technology vendors to expand the disease coverage of its systems. The Indiana University School of Medicine is affiliated with Indiana University Health (IU Health), a medical healthcare system with 17 hospitals and about 33,000 employees in the US.
The collaboration aims to combine Fujifilm’s image processing and AI technology with the Indiana University School of Medicine’s rich diagnostic and clinical expertise to develop medical AI technology, while searching for a system optimized to support diagnosis workflow. The research will initially utilize Fujifilm’s AI technology to segment and quantify muscle atrophy (sarcopenia) in body images, as well as detect and quantify brain lesions in neuroradiology imaging exams.