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MEDICAL IP, prepared for leading ‘data labeling,’ the core of the Korean version of New Deal

MEDICAL IP is ready to lead the 'data labeling' market, which is the core of the Korean version of the New Deal



As the government recently announced the 'Korean version of the New Deal', AI and big data are being highlighted as main industrial keywords that can change society once again.



Accordingly, the importance of 'data labeling' is expected to increase. This is a task to improve the quality of AI learning data by reproducing the processed data that classifies the detailed information in the data.

In the medical field, the introduction of AI technology continues to expand for rapid and accurate analysis of medical image data, such as CT and MRI. MEDICALIP developed MEDIP PRO based on AI medical image analysis and segmentation technology. Last year, MEDICALIP completed certification process, such as the Ministry of Food and Drug Safety (MFDS), FDA, and CE approval, for the first among domestic AI medical imaging companies.

medicalip data labeling

MEDIP PRO is an AI software that not only visualizes two-dimensional medical images in three dimensions but also enables segmentation for each organ region faster and more accurately than humans. It dramatically shortens the labeling process, which used to take several days even if the hospital's skilled workers manually divide it. Therefore, utilizing MEDIP PRO can greatly improve the work efficiency of companies, hospitals, and medical staff.

medicalip data labeling

Data processing and analysis capabilities were also verified through requests and cooperation from several medical institutions. Currently, MEDICALIP has been collaborating with leading domestic hospitals including Seoul National University Hospital, Severance Hospital, Samsung Hospital, and Boramae Hospital. Since last year, only the medical image data that has been precisely labeled in-house has reached 1TB. In addition, by fusion of AI technology and the sophistication of experts, MEDICALIP makes it possible to perform detailed labeling even on high-level X-ray, CT, and MRI images.

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