The extensive digitalization of biomedical images and the implementation of ad hoc digital infrastructures as Picture Archiving and Communication Systems (PACS) need of novel techniques to improve their effectiveness in different e-health tasks. The improvement of processing capabilities of the computer systems allows the use of more accurate techniques to analyze biomedical images. In this context, the image retrieval process represents a key activity. For this purpose, the use of Content Based Image Retrieval (CBIR) techniques on biomedical images repository could improve the effectiveness in specific biomedical image retrieval and support the human decision making process. The aim of our paper is to implement a CBIR system based on local, global and novel deep descriptors extracted from images and compared to prove their efficiency in a real e-health scenario. Several experiments have been carried out using a real dataset and standard measures to show the effectiveness of our approach.
A Content Based Image Retrieval Approach based on Multiple Multimedia Features Descriptors in E-health Environment / Rinaldi, A. M.; Russo, C.. - (2020), pp. 1-6. (Intervento presentato al convegno 15th IEEE International Symposium on Medical Measurements and Applications, MeMeA 2020 tenutosi a ita nel 2020) [10.1109/MeMeA49120.2020.9137356].
A Content Based Image Retrieval Approach based on Multiple Multimedia Features Descriptors in E-health Environment
Rinaldi A. M.
;Russo C.
2020
Abstract
The extensive digitalization of biomedical images and the implementation of ad hoc digital infrastructures as Picture Archiving and Communication Systems (PACS) need of novel techniques to improve their effectiveness in different e-health tasks. The improvement of processing capabilities of the computer systems allows the use of more accurate techniques to analyze biomedical images. In this context, the image retrieval process represents a key activity. For this purpose, the use of Content Based Image Retrieval (CBIR) techniques on biomedical images repository could improve the effectiveness in specific biomedical image retrieval and support the human decision making process. The aim of our paper is to implement a CBIR system based on local, global and novel deep descriptors extracted from images and compared to prove their efficiency in a real e-health scenario. Several experiments have been carried out using a real dataset and standard measures to show the effectiveness of our approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
