| 期刊詳細資料 Journal detailed information |
| 作者(Author) | C.-H. Wei、S.Y Chen、X. Liu |
| 篇名(Article title) | Mammogram retrieval on similar mass lesions |
| 期刊名(Journal name) | Computer Methods and Programs in Biomedicine |
| 國際期刊(International Journal) | SCI |
| 中文摘要(Abstrct) | |
| ABSTRCT | A content-based mammogram retrieval system can support usual comparisons made on images by physicians,
answering similarity queries over images stored in the database. The importance of searching for
similar mammograms lies in the fact that physicians usually try to recall similar cases by seeking images
that are pathologically similar to a given image. This paper presents a content-based mammogram retrieval
system, which employs a query example to search for similar mammograms in the database. In this
system the mammographic lesions are interpreted based on their medical characteristics specified in the
Breast Imaging Reporting and Data System (BI-RADS) standards. A hierarchical similarity measurement
scheme based on a distance weighting function is proposed to model user’s perception and maximizes
the effectiveness of each feature in a mammographic descriptor. A machine learning approach based
on support vector machines and user’s relevance feedback is also proposed to analyze the user’s information
need in order to retrieve target images more accurately. Experimental results demonstrate that the
proposed machine learning approach with Radial Basis Function (RBF) kernel function achieves the best
performance among all tested ones. Furthermore, the results also show that the proposed learning
approach can improve retrieval performance when applied to retrieve mammograms with similar mass
and calcification lesions, respectively. |
| 中文關鍵字(Keyword) | |
| KEYWORD | Content-based image retrieval
BI-RADS standards
Mammogram
PACS
Image indexing
Feature extraction |
| 卷期(Volume No) | Vol. 106 No. 3 |
| 頁數(Page number) | pp. 234~248 |
| 年份(Year) | 2012 |
| 語言(Language) | 英文 English |