Multimodal medical information retrieval with unsupervised rank fusion

Mourão, André; Martins, Flávio; Magalhães, João

doi:10.1016/j.compmedimag.2014.05.006

Cited by 66 publications

(25 citation statements)

References 12 publications

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“…To address this issue, we must perform a new task of pixel-wise rank fusion. Formally, we adopt the recently presented extension of variable length rank lists for multi-media retrieval [46], and fuse per-pixel ranking results as follows [47]:…”

Section: Fault Diagnosis (Fd)mentioning

confidence: 99%

Fault-Diagnosing SLAM for Varying Scale Change Detection

Sugimoto¹,

Yamaguchi²,

Kanji³

2019

Preprint

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In this paper, we present a new fault diagnosis (FD) -based approach for detection of imagery changes that can detect significant changes as inconsistencies between different sub-modules (e.g., self-localizaiton) of visual SLAM. Unlike classical change detection approaches such as pairwise image comparison (PC) and anomaly detection (AD), neither the memorization of each map image nor the maintenance of up-to-date place-specific anomaly detectors are required in this FD approach. A significant challenge that is encountered when incorporating different SLAM sub-modules into FD involves dealing with the varying scales of objects that have changed (e.g., the appearance of small dangerous obstacles on the floor). To address this issue, we reconsider the bag-of-words (BoW) image representation, by exploiting its recent advances in terms of self-localization and change detection. As a key advantage, BoW image representation can be reorganized into any different scaling by simply cropping the original BoW image. Furthermore, we propose to combine different self-localization modules with strong and weak BoW features with different discriminability, and to treat inconsistency between strong and weak self-localization as an indicator of change. The efficacy of the proposed approach for FD with/without AD and/or PC was experimentally validated.

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Section: Fault Diagnosis (Fd)mentioning

confidence: 99%

Fault-Diagnosing SLAM for Varying Scale Change Detection

Sugimoto¹,

Yamaguchi²,

Kanji³

2019

Preprint

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show abstract

“…The latter may be based on the score of each result entry (representing the system's individual appreciation of relevance for that result) or be based on the rank of said result on the full list. Other algorithms that do not fit in either case also exist, such as the inverted squared rank (ISR) [20].…”

Section: Multi-query and Fusion Techniquesmentioning

confidence: 99%

A Multimodal Search Engine for Medical Imaging Studies

et al. 2016

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“…In contrast to this understanding of the retrieval process, interactive approaches consider the intervention of the user to refine or fine tune the behavior of the system in order to obtain a better definition of user's needs, thus, improving the relevance of retrieved items. The system proposed by Mourau and his colleagues [20] enables the user to add new keywords taken from the MeSH thesaurus before performing query expansion, although in this study keywords are proposed automatically. This idea of allowing the user to refine the query is not new, as interactive query expansion was proposed more than thirty years ago [21].…”

Section: Introductionmentioning

confidence: 99%

An Integrated Approach to Biomedical Term Identification Systems

et al. 2020

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In this paper a novel architecture to build biomedical term identification systems is presented. The architecture combines several sources of information and knowledge bases to provide practical and exploration-enabled biomedical term identification systems. We have implemented a system to evidence the convenience of the different modules considered in the architecture. Our system includes medical term identification, retrieval of specialized literature and semantic concept browsing from medical ontologies. By applying several Natural Language Processing (NLP) technologies, we have developed a prototype that offers an easy interface for helping to understand biomedical specialized terminology present in Spanish medical texts. The result is a system that performs term identification of medical concepts over any textual document written in Spanish. It is possible to perform a sub-concept selection using the previously identified terms to accomplish a fine-tune retrieval process over resources like SciELO, Google Scholar and MedLine. Moreover, the system generates a conceptual graph which semantically relates all the terms found in the text. In order to evaluate our proposal on medical term identification, we present the results obtained by our system using the MANTRA corpus and compare its performance with the Freeling-Med tool.

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Multimodal medical information retrieval with unsupervised rank fusion

Cited by 66 publications

References 12 publications

Fault-Diagnosing SLAM for Varying Scale Change Detection

Fault-Diagnosing SLAM for Varying Scale Change Detection

A Multimodal Search Engine for Medical Imaging Studies

An Integrated Approach to Biomedical Term Identification Systems

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