1. Utilization of R&D results

● Utilization of standardized open brain-vessel convergence image database

1) Primary dataset: Raw Database

Multimodal MR raw data of disease-free healthy people and cerebrovascular patients are provided through an anonymization process while observing the regulations related to personal information protection so that it can be used for various research purposes, including the health information of subjects

2) Secondary dataset: Integrated brain-vessel imaging database

Research and diagnosis of various cerebrovascular diseases based on the provided secondary database of length, tortuosity, SOAM, change in curvature, thickness, cross-sectional area, volume, and characteristics of brain lesions by territory extracted through the developed software and applicable to treatment.

3) Availability of big data base large-scale cohort collection

It is possible to build a large-scale enormous data cohort by continuously reinforcing and expanding the database by collecting brain images and clinical data from multi-institutional and in-hospital subjects.

● Contents and plans of patent and technology transfer for cerebrovascular image fusion database construction

- Automated preprocessing algorithm of various multimodal MR images for standardized database construction

- software that uses deep learning technology to segment, skeletize, and dissect existing cerebrovascular images

- Multi-scale quantitative feature extraction algorithm from patient image data

- Analysis algorithm for discovering high-dimensional feature biomarkers using the developed cerebrovascular fusion image database

- User-friendly GUI advancement and visualization technology

● Disclosure of R&D result DB

- Web-based information sharing and research sharing to build an open data warehouse

By distributing the cerebrovascular analysis technique platform to each institution, it analyzes patient data, creates secondary processed data, and transmits it back to the host institution to protect the patient’s personal information and build an open data warehouse so that a large number of researchers can utilize the data

● Application of R&D results and expansion of convergence research with other disciplines

- We plan to explore the general applicability of the model obtained through expanded application to other imaging techniques such as CT angiography or catheter-based angiography and collaboration with other institutions.

- By constructing a database to which an AI-based cerebrovascular analysis algorithm is applied, it is possible to unify it into an integrated database for patient diagnosis in the long term by presenting a standard (draft) for establishing a domestic and foreign clinical database.

- It is possible to present improved diagnostic biomarkers for vascular brain disease. Ultimately, it is intended to be applied to the medical field after clinical verification as an auxiliary function of the patient diagnosis system.

- By grafting genomic medicine technology, it is intended to expand into multidisciplinary research fields with other disciplines. It is possible to build a new concept of brain disease diagnosis and treatment platform through the convergence of this project and other disciplines.

2. Prospective benefits

Category	Prospective benefits
Academic and technological aspects	● Improvement of brain disease research level and performance improvement - The combination of processed data and deep learning technology will improve the quantitative and qualitative level of brain disease research and the performance of related diagnostic models. - It lays the groundwork for the direct study of major cerebral arteries (vessels at the muscular artery level). ● Development of brain disease diagnosis and treatment technology by standardization of quantitative index system of cerebrovascular imaging - Through this, it is expected that if the diagnosis is accurate and subdivided, reading errors can be minimized, and treatment technology development will be facilitated. ● Expectations for the development of patient-tailored medical business and precision medicine - The development of precision medicine can be expected through this detailed project. Advances in precision medicine are expected to contribute to the improvement of disease prediction, understanding, diagnosis, and treatment. ● Differentiation from existing brain image databases - The developed brain-vessel image database is an artificial intelligence-based platform that analyzes brain images according to the characteristics of blood vessels in the brain and extracts various imaging features. In particular, employing the pre-processing process for analysis of input data, the post-processing process for extracting the secondary processing data, and the presentation of visualization by combining patient clinical information and result data, we secure the competence in clinical research using patient images is demonstrated.
Economical and industrial aspects	● With the global medical technology market through strengthening brain research - A new concept of brain disease diagnosis and treatment platform can be additionally built through the convergence of the warehouse developed through this research, artificial intelligence, and genomic medicine technology. Promote convergence research with heterogeneous technologies and create new industries based on future technologies by establishing a cluster of brain-related medical sectors.
Socio-economical aspects	● Reduction of social and economic costs such as medical expenses and labor loss due to brain disease - The development of automation algorithms is expected to improve the quality of life by reducing time and economic costs for patients, caregivers, and doctors making diagnoses. ● Improving the quality of public health by using a high-performance brain disease diagnosis system