IFM3IRS: Information fusion retrieval system with knowledge-assisted text and visual features based on medical conceptual model

Verfasser / Beitragende:
[Hizmawati Madzin, Roziati Zainuddin, Nurfadhlina Sharef]
Ort, Verlag, Jahr:
2015
Enthalten in:
Multimedia Tools and Applications, 74/11(2015-06-01), 3651-3674
Format:
Artikel (online)
ID: 605447608
LEADER caa a22 4500
001 605447608
003 CHVBK
005 20210128100132.0
007 cr unu---uuuuu
008 210128e20150601xx s 000 0 eng
024 7 0 |a 10.1007/s11042-013-1792-2  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s11042-013-1792-2 
245 0 0 |a IFM3IRS: Information fusion retrieval system with knowledge-assisted text and visual features based on medical conceptual model  |h [Elektronische Daten]  |c [Hizmawati Madzin, Roziati Zainuddin, Nurfadhlina Sharef] 
520 3 |a The technology of medical data production has been rapidly changed over the past few years. Modern computer technology has created the possibility of creating multi-modal medical images. Medical data often contain multi-modal information such as visual information (image) as well as textual information. Both types of information are important for medical retrieval system (MRS). Due to the information limitation at different levels of sources, the application of information fusion becomes a real need in medical application. In this research, an information fusion framework was built to develop the multi-modality medical image retrieval system (IFM3IRS). The framework utilizes two sources of information involving text and visual-based retrieval process. The application is based on sequential order where the result from text-based process will automatically be the input in visual-based process. The main contributions of this paper are the development of a new ranking model called MedHieCon ranking model which applies semantic concepts of modality, anatomy and pathology in text-based process and also the learning approach of medical images using medical concept model in visual-based process. ImageCLEFmed 2010 data collection was used to evaluate IFM3IRS and it shows that our information fusion framework is in top list among other researchers. Although text-based retrieval system has proven to be a better performance in MRS; it is significant to determine the overall performance improvements which include the fusion of text and image. 
540 |a Springer Science+Business Media New York, 2013 
690 7 |a Information fusion  |2 nationallicence 
690 7 |a Late fusion technique  |2 nationallicence 
690 7 |a Text-based retrieval  |2 nationallicence 
690 7 |a Visual-based image retrieval  |2 nationallicence 
690 7 |a Query expansion  |2 nationallicence 
690 7 |a Boolean model  |2 nationallicence 
690 7 |a Supervised classification  |2 nationallicence 
700 1 |a Madzin  |D Hizmawati  |u Multimedia Department, Faculty of Computer Science & Information Technology, University Putra Malaysia, Serdang, Malaysia  |4 aut 
700 1 |a Zainuddin  |D Roziati  |u Artificial Intelligence Department, Faculty of Computer Science & Information Technology, University of Malaya, Kuala Lumpur, Malaysia  |4 aut 
700 1 |a Sharef  |D Nurfadhlina  |u Computer Science Department, Faculty of Computer Science & Information Technology, University Putra Malaysia, Serdang, Malaysia  |4 aut 
773 0 |t Multimedia Tools and Applications  |d Springer US; http://www.springer-ny.com  |g 74/11(2015-06-01), 3651-3674  |x 1380-7501  |q 74:11<3651  |1 2015  |2 74  |o 11042 
856 4 0 |u https://doi.org/10.1007/s11042-013-1792-2  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s11042-013-1792-2  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Madzin  |D Hizmawati  |u Multimedia Department, Faculty of Computer Science & Information Technology, University Putra Malaysia, Serdang, Malaysia  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Zainuddin  |D Roziati  |u Artificial Intelligence Department, Faculty of Computer Science & Information Technology, University of Malaya, Kuala Lumpur, Malaysia  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Sharef  |D Nurfadhlina  |u Computer Science Department, Faculty of Computer Science & Information Technology, University Putra Malaysia, Serdang, Malaysia  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Multimedia Tools and Applications  |d Springer US; http://www.springer-ny.com  |g 74/11(2015-06-01), 3651-3674  |x 1380-7501  |q 74:11<3651  |1 2015  |2 74  |o 11042