Medical Image Retrieval in Healthcare Social Networks

Riadh Bouslimi, Mouhamed Gaith Ayadi and Jalel Akaichi
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Riadh Bouslimi: ISG, Tunis, Tunisia
Mouhamed Gaith Ayadi: ISG, Tunis, Tunisia
Jalel Akaichi: ISG, Tunis, Tunisia

International Journal of Healthcare Information Systems and Informatics (IJHISI), 2018, vol. 13, issue 2, 13-28

Abstract: In this article, the authors present a multimodal research model to research medical images based on multimedia information that is extracted from a radiological collaborative social network. The opinions shared on a medical image in a medico-social network is a textual description which in most cases requires cleaning by using a medical thesaurus. In addition, they describe the textual description and medical image in a TF-IDF weight vector using a “bag-of-words” approach. The authors then use latent semantic analysis to establish relationships between textual terms and visual terms in shared opinions on the medical image. The model is evaluated against the ImageCLEFmedbaseline, which is the ground truth for the experiments. The authors have conducted numerous experiments with different descriptors and many combinations of modalities. The analysis of results shows that when the model is based on two methods it can increase the performance of a research system based on a single modality both visually or textually.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jhisi0:v:13:y:2018:i:2:p:13-28

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