A bag of semantic words model for medical content-based retrieval

Sidong Liu, Weidong Cai, Yang Song, Sonia Pujol, Ron Kikinis, Dagan Feng

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

Abstract

The bag of visual words model has been widely used in content-based image retrieval. However, when it is applied to medical domain, it potentially has several limitations, e.g., some ordinary feature descriptors may not be able to capture the subtle characteristics of medical images; there is a semantic gap between the low-level features and the medical concepts; the emerging multi-modal data pose challenges on current retrieval framework and urge us to extend the possibilities to combine and analyze the multi-modal data. In an attempt to address these issues, we proposed a bag of semantic words model for medical content-based retrieval in this study. We built the high-level semantic features from the low-level visual features by a three-step pipeline. We first extracted a set of low-level features pertaining to the disease symptoms from the medical images. We then translated the low-level features to symptom severity degrees by symptom quantization. Finally, the high-level semantic words were built through learning the patterns of the symptoms. The proposed model was evaluated using 331 multi-modal neuroimaging datasets from the ADNI database. The preliminary results show that the proposed bag of semantic words model could extract the semantic information from medical images and outperformed the state-of-the-art medical content-based retrieval methods.
Original languageEnglish
Title of host publicationInternational Workshop on Medical Content-Based Retrieval for Clinical Decision Support 2013
Number of pages8
Publication statusPublished - 26 Sep 2013
Externally publishedYes
EventMICCAI Workshop on Medical Content-based Retrieval for Clinical Decision Support - Nagoya, Japan
Duration: 27 Sep 2013 → …

Conference

ConferenceMICCAI Workshop on Medical Content-based Retrieval for Clinical Decision Support
CountryJapan
CityNagoya
Period27/09/13 → …

Fingerprint

Dive into the research topics of 'A bag of semantic words model for medical content-based retrieval'. Together they form a unique fingerprint.

Cite this