All-in-one platform for AI R&D in medical imaging, encompassing data collection, selection, annotation, and pre-processing
Changhee Han, Kyohei Shibano, Wataru Ozaki, Keishiro Osaki, Takafumi, Haraguchi, Daisuke Hirahara, Shumon Kimura, Yasuyuki Kobayashi, Gento Mogi

TL;DR
This paper introduces a comprehensive platform for medical imaging AI R&D that addresses data imbalance by including under-represented Asian data, offering ready-to-use datasets, and integrating advanced technologies like blockchain and generative AI.
Contribution
It presents the first commercial platform covering data collection, selection, annotation, and pre-processing, with a focus on Asian data and innovative data security and synthesis methods.
Findings
Established a platform with diverse Asian medical imaging data
Provided ready-to-use datasets for AI development
Plans to incorporate blockchain and generative AI for data security and synthesis
Abstract
Deep Learning is advancing medical imaging Research and Development (R&D), leading to the frequent clinical use of Artificial Intelligence/Machine Learning (AI/ML)-based medical devices. However, to advance AI R&D, two challenges arise: 1) significant data imbalance, with most data from Europe/America and under 10% from Asia, despite its 60% global population share; and 2) hefty time and investment needed to curate proprietary datasets for commercial use. In response, we established the first commercial medical imaging platform, encompassing steps like: 1) data collection, 2) data selection, 3) annotation, and 4) pre-processing. Moreover, we focus on harnessing under-represented data from Japan and broader Asia, including Computed Tomography, Magnetic Resonance Imaging, and Whole Slide Imaging scans. Using the collected data, we are preparing/providing ready-to-use datasets for medical…
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Taxonomy
TopicsRadiomics and Machine Learning in Medical Imaging
MethodsFocus
