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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Sukno, Federico Mateo; Domínguez Bajo, Mónica; Ruiz, Adrià; Schiller, Dominik; +4 Authors

    The development of conversational agents with human interaction capabilities requires advanced affective state recognition integrating non-verbal cues from the different modalities constituting what in human communication we perceive as an overall affective state. Each of the modalities is often handled by a different subsystem that conveys only a partial interpretation of the whole and, as such, is evaluated only in/nterms of its partial view. To tackle this shortcoming, we investigate the generation of a unified multimodal annotation schema of non-verbal cues from the perspective of an interdisciplinary group of experts. We aim at obtaining a common ground-truth with a unique representation using the Valence and Arousal space and a discrete non-linear scale of values. The proposed annotation schema is demonstrated on/na corpus in the health-care domain but is scalable to other purposes. Preliminary results on inter-rater variability show a positive correlation of consensus level with high (absolute) values of Valence and Arousal as well as with the number of annotators labeling a given video sequence. This work is partly supported by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502) and is part of the Kristina project funded by the European UnionˇSs Horizon 2020 research and innovation programme under grant agreement No 645012.

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    https://doi.org/10.1145/292700...
    Other literature type . Conference object . 2016 . Peer-reviewed
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    OPUS Augsburg
    Part of book or chapter of book . 2016
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      https://doi.org/10.1145/292700...
      Other literature type . Conference object . 2016 . Peer-reviewed
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      OPUS Augsburg
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    Authors: Aurelie Herbelot; Ekaterina Kochmar;

    In this paper we discuss three key points related to error detection (ED) in learners' English. We focus on content word ED as one of the most challenging tasks in this area, illustrating our claims on adjective–noun (AN) combinations. In particular, we (1) investigate the role of context in accurately capturing semantic anomalies and implement a system based on distributional topic coherence, which achieves state-of-the-art accuracy on a standard test set; (2) thoroughly investigate our system's performance across individual adjective classes, concluding that a class-dependent approach is beneficial to the task; (3) discuss the data size bottleneck in this area, and highlight the challenges of automatic error generation for content words.

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    Archive ouverte UNIGE
    Part of book or chapter of book . 2016
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    Apollo
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      Apollo
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Wojatzki, Michael; Mohammad, Saif M.; Zesch, Torsten; Kiritchenko, Svetlana;

    Understanding public opinion on complex controversial issues such as 'Legalization of Marijuana' and 'Gun Rights' is of considerable importance for a number of objectives such as identifying the most divisive facets of the issue, developing a consensus, and making informed policy decisions. However, an individual's position on a controversial issue is often not just a binary support-or-oppose stance on the issue, but rather a conglomerate of nuanced opinions and beliefs on various aspects of the issue. These opinions and beliefs are often expressed qualitatively in free text in issue-focused surveys or on social media. However, quantifying vast amounts of qualitative information remains a significant challenge. The goal of this work is to provide a new approach for quantifying qualitative data for the understanding of controversial issues. First, we show how we can engage people directly through crowdsourcing to create a comprehensive dataset of assertions (claims, opinions, arguments, etc.) relevant to an issue. Next, the assertions are judged for agreement and strength of support or opposition, again by crowdsourcing. The collected Dataset of Nuanced Assertions on Controversial Issues (NAoCI dataset) consists of over 2,000 assertions on sixteen different controversial issues. It has over 100,000 judgments of whether people agree or disagree with the assertions, and of about 70,000 judgments indicating how strongly people support or oppose the assertions. This dataset allows for several useful analyses that help summarize public opinion. Across the sixteen issues, we find that when people judge a large set of assertions they often do not disagree with the individual assertions that the opposite side makes, but that they differently judge the relative importance of these assertions. We show how assertions that cause dissent or consensus can be identified by ranking the whole set of assertions based on the collected judgments. We also show how free-text assertions in social media can be analyzed in conjunction with the crowdsourced information to quantify and summarize public opinion on controversial issues. LREC 2018, Eleventh International Conference on Language Resources and Evaluation, 7-12 May 2018, Miyazaki, Japan

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    NRC Publications Archive
    Other literature type . 2018
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    https://doi.org/10.17185/duepu...
    Other literature type . 2018
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Universitätsbibliogr...arrow_drop_down
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      NRC Publications Archive
      Other literature type . 2018
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      https://doi.org/10.17185/duepu...
      Other literature type . 2018
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    Authors: Kowatsch, Tobias; id_orcid0000-0001-5939-4145; Wahle, Fabian; Filler, Andreas;

    Work-related stress has the potential to increase the risk of chronic stress, major depression and other non-communicable diseases. Organizational stress monitoring usually applies long-term self-report instruments that are designed in a retrospective manner, and thus, is obtrusive, time-consuming and, most important, fails to detect and predict short-term episodes of stress. To ad- dress this shortcoming, we apply design science research with the goal to design, implement and evaluate a stress management service for knowledge workers (stressOUT) that senses the degree of work-related stress solely based on mouse movements. Using stress theory as justificatory knowledge, we implemented stressOUT that tracks mouse movements and perceived stress levels randomly twice a day with the goal to learn features of mouse movements that are related to stress perceptions. Results of a first longitudinal field study indicate that mouse cursor speed is negatively related to perceived stress. Future work is discussed. Designing the Digital Transformation. DESRIST 2017 Research in Progress Proceedings KIT Scientific Working Papers, 64 ISSN:2194-1629

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    Research Collection
    Conference object . 2017
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    Cork Open Research Archive (CORA)
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    ETH Zürich Research Collection
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    Alexandria Research Platform
    Part of book or chapter of book . 2017
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    Authors: Milchevski, Evica; Anand, Avishek; Michel, Sebastian;

    We consider the problem of processing similarity queries over a set of top-k rankings where the query ranking and the similarity threshold are provided at query time. Spearman’s Footrule distance is used to compute the similarity between rankings, considering how well rankings agree on the positions (ranks) of ranked items (i.e., the L1 distance). This setup allows the application of metric index structures such as M- or BK-trees and, alternatively, enables the use of traditional inverted indices for retrieving rankings that overlap (in items) with the query. Although both techniques are reasonable, they come with individual drawbacks for our specific problem. In this paper, we propose a hybrid indexing strategy, which blends inverted indices and metric space indexing, resulting in a structure that resembles both indexing methods with tunable emphasis on one or the other. To find the sweet spot, we propose an assumption-lean but highly accurate (empirically validated) cost model through theoretical analysis. We further present optimizations to the inverted index component, for early termination and minimizing bookkeeping. The performance of the proposed algorithms, hybrid variants, and competitors is studied in a comprehensive evaluation using real-world benchmark data consisting of Web-search–result rankings and entity rankings based on Wikipedia.

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    https://doi.org/10.15488/5478...
    Part of book or chapter of book . 2015
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      https://doi.org/10.15488/5478...
      Part of book or chapter of book . 2015
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    Authors: Brenner, A.; Kutafina, Ekaterina; Jonas, S. M.;

    Studies in health technology and informatics; 171-175 (2018). doi:10.3233/978-1-61499-852-5-171

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    https://doi.org/10.18154/rwth-...
    Part of book or chapter of book . 2018
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      https://doi.org/10.18154/rwth-...
      Part of book or chapter of book . 2018
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    Authors: Doshi, Trushali; Soraghan, John; Grose, Derek; MacKenzie, Kenneth; +1 Authors

    Magnetic resonance imaging (MRI) is a widely used imaging modality to extract tumour regions to assist in radiotherapy and surgery planning. Extraction of a tongue base tumour from MRI is challenging due to variability in its shape, size, intensities and fuzzy boundaries. This paper presents a new automatic algorithm that is shown to be able to extract tongue base tumour from gadolinium-enhanced T1-weighted (T1+Gd) MRI slices. In this algorithm, knowledge of tumour location is added to the objective function of standard fuzzy c-means (FCM) to extract the tumour region. Experimental results on 9 real MRI slices demonstrate that there is good agreement between manual and automatic extraction results with dice similarity coefficient (DSC) of 0.77±0.08.

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    ZENODO
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Sukno, Federico Mateo; Domínguez Bajo, Mónica; Ruiz, Adrià; Schiller, Dominik; +4 Authors

    The development of conversational agents with human interaction capabilities requires advanced affective state recognition integrating non-verbal cues from the different modalities constituting what in human communication we perceive as an overall affective state. Each of the modalities is often handled by a different subsystem that conveys only a partial interpretation of the whole and, as such, is evaluated only in/nterms of its partial view. To tackle this shortcoming, we investigate the generation of a unified multimodal annotation schema of non-verbal cues from the perspective of an interdisciplinary group of experts. We aim at obtaining a common ground-truth with a unique representation using the Valence and Arousal space and a discrete non-linear scale of values. The proposed annotation schema is demonstrated on/na corpus in the health-care domain but is scalable to other purposes. Preliminary results on inter-rater variability show a positive correlation of consensus level with high (absolute) values of Valence and Arousal as well as with the number of annotators labeling a given video sequence. This work is partly supported by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502) and is part of the Kristina project funded by the European UnionˇSs Horizon 2020 research and innovation programme under grant agreement No 645012.

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    http://repositori.upf.edu/bits...
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    https://doi.org/10.1145/292700...
    Other literature type . Conference object . 2016 . Peer-reviewed
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      https://doi.org/10.1145/292700...
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      OPUS Augsburg
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Aurelie Herbelot; Ekaterina Kochmar;

    In this paper we discuss three key points related to error detection (ED) in learners' English. We focus on content word ED as one of the most challenging tasks in this area, illustrating our claims on adjective–noun (AN) combinations. In particular, we (1) investigate the role of context in accurately capturing semantic anomalies and implement a system based on distributional topic coherence, which achieves state-of-the-art accuracy on a standard test set; (2) thoroughly investigate our system's performance across individual adjective classes, concluding that a class-dependent approach is beneficial to the task; (3) discuss the data size bottleneck in this area, and highlight the challenges of automatic error generation for content words.

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    Archive ouverte UNIGE
    Part of book or chapter of book . 2016
    License: CC BY
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    Apollo
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      Archive ouverte UNIGE
      Part of book or chapter of book . 2016
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      Apollo
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Wojatzki, Michael; Mohammad, Saif M.; Zesch, Torsten; Kiritchenko, Svetlana;

    Understanding public opinion on complex controversial issues such as 'Legalization of Marijuana' and 'Gun Rights' is of considerable importance for a number of objectives such as identifying the most divisive facets of the issue, developing a consensus, and making informed policy decisions. However, an individual's position on a controversial issue is often not just a binary support-or-oppose stance on the issue, but rather a conglomerate of nuanced opinions and beliefs on various aspects of the issue. These opinions and beliefs are often expressed qualitatively in free text in issue-focused surveys or on social media. However, quantifying vast amounts of qualitative information remains a significant challenge. The goal of this work is to provide a new approach for quantifying qualitative data for the understanding of controversial issues. First, we show how we can engage people directly through crowdsourcing to create a comprehensive dataset of assertions (claims, opinions, arguments, etc.) relevant to an issue. Next, the assertions are judged for agreement and strength of support or opposition, again by crowdsourcing. The collected Dataset of Nuanced Assertions on Controversial Issues (NAoCI dataset) consists of over 2,000 assertions on sixteen different controversial issues. It has over 100,000 judgments of whether people agree or disagree with the assertions, and of about 70,000 judgments indicating how strongly people support or oppose the assertions. This dataset allows for several useful analyses that help summarize public opinion. Across the sixteen issues, we find that when people judge a large set of assertions they often do not disagree with the individual assertions that the opposite side makes, but that they differently judge the relative importance of these assertions. We show how assertions that cause dissent or consensus can be identified by ranking the whole set of assertions based on the collected judgments. We also show how free-text assertions in social media can be analyzed in conjunction with the crowdsourced information to quantify and summarize public opinion on controversial issues. LREC 2018, Eleventh International Conference on Language Resources and Evaluation, 7-12 May 2018, Miyazaki, Japan

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    NRC Publications Archive
    Other literature type . 2018
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    https://doi.org/10.17185/duepu...
    Other literature type . 2018
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      NRC Publications Archive
      Other literature type . 2018
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      https://doi.org/10.17185/duepu...
      Other literature type . 2018
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    Authors: Kowatsch, Tobias; id_orcid0000-0001-5939-4145; Wahle, Fabian; Filler, Andreas;

    Work-related stress has the potential to increase the risk of chronic stress, major depression and other non-communicable diseases. Organizational stress monitoring usually applies long-term self-report instruments that are designed in a retrospective manner, and thus, is obtrusive, time-consuming and, most important, fails to detect and predict short-term episodes of stress. To ad- dress this shortcoming, we apply design science research with the goal to design, implement and evaluate a stress management service for knowledge workers (stressOUT) that senses the degree of work-related stress solely based on mouse movements. Using stress theory as justificatory knowledge, we implemented stressOUT that tracks mouse movements and perceived stress levels randomly twice a day with the goal to learn features of mouse movements that are related to stress perceptions. Results of a first longitudinal field study indicate that mouse cursor speed is negatively related to perceived stress. Future work is discussed. Designing the Digital Transformation. DESRIST 2017 Research in Progress Proceedings KIT Scientific Working Papers, 64 ISSN:2194-1629

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      Cork Open Research Archive (CORA)
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      Part of book or chapter of book . 2017
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    Authors: Milchevski, Evica; Anand, Avishek; Michel, Sebastian;

    We consider the problem of processing similarity queries over a set of top-k rankings where the query ranking and the similarity threshold are provided at query time. Spearman’s Footrule distance is used to compute the similarity between rankings, considering how well rankings agree on the positions (ranks) of ranked items (i.e., the L1 distance). This setup allows the application of metric index structures such as M- or BK-trees and, alternatively, enables the use of traditional inverted indices for retrieving rankings that overlap (in items) with the query. Although both techniques are reasonable, they come with individual drawbacks for our specific problem. In this paper, we propose a hybrid indexing strategy, which blends inverted indices and metric space indexing, resulting in a structure that resembles both indexing methods with tunable emphasis on one or the other. To find the sweet spot, we propose an assumption-lean but highly accurate (empirically validated) cost model through theoretical analysis. We further present optimizations to the inverted index component, for early termination and minimizing bookkeeping. The performance of the proposed algorithms, hybrid variants, and competitors is studied in a comprehensive evaluation using real-world benchmark data consisting of Web-search–result rankings and entity rankings based on Wikipedia.

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    https://doi.org/10.15488/5478...
    Part of book or chapter of book . 2015
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Institutionelles Rep...arrow_drop_down
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      https://doi.org/10.15488/5478...
      Part of book or chapter of book . 2015
      License: CC BY NC ND
      Data sources: Datacite
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    Authors: Brenner, A.; Kutafina, Ekaterina; Jonas, S. M.;

    Studies in health technology and informatics; 171-175 (2018). doi:10.3233/978-1-61499-852-5-171

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    https://doi.org/10.18154/rwth-...
    Part of book or chapter of book . 2018
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Publikationsserver d...arrow_drop_down
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      https://doi.org/10.18154/rwth-...
      Part of book or chapter of book . 2018
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    Authors: Doshi, Trushali; Soraghan, John; Grose, Derek; MacKenzie, Kenneth; +1 Authors

    Magnetic resonance imaging (MRI) is a widely used imaging modality to extract tumour regions to assist in radiotherapy and surgery planning. Extraction of a tongue base tumour from MRI is challenging due to variability in its shape, size, intensities and fuzzy boundaries. This paper presents a new automatic algorithm that is shown to be able to extract tongue base tumour from gadolinium-enhanced T1-weighted (T1+Gd) MRI slices. In this algorithm, knowledge of tumour location is added to the objective function of standard fuzzy c-means (FCM) to extract the tumour region. Experimental results on 9 real MRI slices demonstrate that there is good agreement between manual and automatic extraction results with dice similarity coefficient (DSC) of 0.77±0.08.

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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CORE (RIOXX-UK Aggre...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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