내용기반 검색 기법을 이용한 인터넷 기반 유방종양 조직병리영상 검색 시스템 개발 = Development of Histopathological Breast Tumor Image Retrieval System Based on Internet Using a Content-based Retrieval Method

다국어 초록 (Multilingual Abstract)

Objective: We have developed breast tumor image retrieval system using content-based retrieval method. It compares the breast tumor image with Fibrocystic Change images, Ductal Carcinoma in Situ images and Invasive Ductal Carcinoma images and find most similar one. Since the final diagnosis for breast tumor image is done only by pathologist manually, this system can provide the objectivity and the reproducibility for determining and diagnosing the breast tumor. Methods: The breast tumor image features used in the content-based image retrieval are color feature, texture feature and texture features of wavelet transformed images. And the system can be accessed through the internet. We used Windows 2003 as an operating system, Internet Information Server 6.0 as Web a server and ms-sql server 2000 as a database server. Also we use ActiveX Data Object to connect database easily. Result: We evaluated the recall and precision performance of the system according to the combinations of feature types and usage of partial or whole image. Results showed that the use of multiple features and whole image gave consistently higher rates compared to the use of single feature and partial image. Conclusion: This retrieval system can help pathologist determine the type of breast tumor more efficiently. Also it is working based on the internet, we can use it for researching and teaching in pathology later.

참고문헌 (Reference)

1 "Region-based image retrieval using integrated color,shape,and location index" 94 : 193-233, 2004

2 "New methods for image analysis of tissue sections [dissertation]" Uppsala University 1996

3 "Image retrieval by texture similarity" 36 : 665-679, 2003

4 "Image classification using color,texture and regions" 21 : 759-776, 2003

5 "Grading of transitional cell bladder carcinoma by texture analysis of histological section" 6 : 327-343, 1994

6 "Design of a two-stage content-based image retrieval system using texture similarity" 40 : 81-96, 2004

7 "Content-based cell image retrieval using automated extraction" 7 (7): 404-415, 2000

8 "Computing,explaining and visualizing shape similarity in content- based image retrieval" 10 : 1-19, 2004

9 "Classification of cell and tissue images in breast tumor [dissertation]" Inje University 2002

10 "Analysis and extraction of significant features for creating an optimized classifier of bladder carcinoma cell histological images [dissertation]" Inje University 2001

11 "Algorithms for image processing and computer vision" Wiley Computer Publishing 150-174, 1997

12 "A region -based database system using colour and texture" 20 : 1323-1330, 1999