Upgrading of the CT image database by automatically attaching the meta-information

2016 Fiscal Year Final Research Report

• Project/Area Number: 26330134
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Multimedia database
• Research Institution: Gifu University
• Principal Investigator: ZHOU XIANGRONG 岐阜大学, 大学院医学系研究科, 助教 (00359738)
• Research Collaborator: FUJITA Hiroshi ; AZUMA Kagaku ; KATO Hiroki ; WANG Song
• Project Period (FY): 2014-04-01 – 2017-03-31
• Keywords: データベースシステム / 医用画像処理 / 解剖学的構造の自動認識

Outline of Final Research Achievements

In this work, we collected a large number of three-dimensional CT images. The anatomical structures and local image appearances in those images were arranged. We developed a machine-learning based approach to recognize and extract anatomical structures automatically from the CT images, and integrated that information into the database. We applied the database to predicting the risk of breast cancers and vertebral fractures in preventive medicine, and 3D printing of the patient specific models for uterus surgical planning.The aim of this work of “Upgrading of the CT image database by automatically attaching the meta-information” was almost realized.

Free Research Field

総合領域　情報学・メディア情報学・データベース