Predicting abnormalities in abdominal organs through prognostic factors extracted from image data

• Project/Area Number: 24K21121
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 90130:Medical systems-related
• Research Institution: The University of Tokyo
• Principal Investigator: ALAM MD・ASHRAFUL 東京大学, 医学部附属病院, 特任研究員 (80866632)
• Project Period (FY): 2024-04-01 – 2027-03-31
• Project Status: Granted (Fiscal Year 2024)
• Budget Amount: ¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000); Fiscal Year 2026: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000); Fiscal Year 2025: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000); Fiscal Year 2024: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
• Keywords: Medical image / Predict abnormalities / Abdominal organs / Machine learning / Segmentation

Outline of Research at the Start

Imaging biomarkers of response play a crucial role as an alternative to assessing pathological responses. Using AI, we have been able to segment images accurately. Using this segmented organ's information to predict a patient's future outcome of disease is the main purpose of this research project.