Colorectal cancer is the most common cancer in
NEC has been working with the National Cancer Center Japan since 2016 to contribute to resolving this issue. NEC has now developed software that can automatically mark potential lesions based on the use of AI to learn from endoscopic images of more than 10,000 lesions, as well as learning from the observations of expert physicians (*4). This software was developed by applying NEC's AI technologies, 'NEC the WISE,' and its face recognition technology, which is highly evaluated by the
Software features include the following:
1. Compatibility with the endoscopy systems of three leading companies and usability in any examination room
This software can be connected to endoscopes from three leading endoscope manufacturers (*6). By simply connecting an existing endoscope to a monitor and terminal equipped with the software, users can start using it immediately. Moreover, since it is compatible with various endoscopes and easy to prepare, systems can be transferred within different rooms and used efficiently wherever there is an examination.
2. High visibility and flexible interface
The system marks the lesion candidates with a notification sound and marking. Notification sounds, volume, and marker colors can be customized at any time to the user's preference. The system can be operated intuitively with a high-visibility user interface, allowing users to smoothly proceed with examinations.
Going forward, as a company that creates social value, NEC aims to promote a healthy, and sustainable society, where individuals can thrive from the utilization of advanced IT technologies.
(*1) According to statistics from the National Cancer Research Center Japan (Japanese text only)
new windowhttps://ganjoho.jp/reg_stat/statistics/stat/summary.html
(*2) According to United European Gastroenterology
new windowhttps://ueg.eu/p/78#
(*3) Rex DK, Cutler CS, Lemmel GT, et al. Colonoscopic miss rates of adenomas determined by back-to-back colonoscopies. Gastroenterology. 1997;112(1):24-28
(*4) Yamada M, Saito Y, Imaoka H,et al. Development of a real-time endoscopic image diagnosis support system using deep learning technology in colonoscopy. Sci Rep. 2019;9:14465
(*5) NEC Face Recognition Technology Ranks First in NIST Accuracy Testing
https://www.nec.com/en/press/201910/global_20191003_01.html
(*6) Connectivity and operations have been confirmed with the following endoscopes
Olympus EVIS LUCERA ELITE Video System Center CV-290
FUJIFILM ELUXEO video processor VP-7000
PENTAX Medical OPTIVISTA EPK-i7010 video processor
Product name: WISE VISION Endoscopy
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