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International Workshop on Graph-Based Representations in Pattern Recognition

GbRPR 2007: Graph-Based Representations in Pattern Recognition pp 49–60 Cite as

Graph Based Shapes Representation and Recognition

  • Rashid Jalal Qureshi 1 ,
  • Jean-Yves Ramel 1 &
  • Hubert Cardot 1  
  • Conference paper

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9 Citations

Part of the Lecture Notes in Computer Science book series (LNIP,volume 4538)

In this paper, we propose to represent shapes by graphs. Based on graphic primitives extracted from the binary images, attributed relational graphs were generated. Thus, the nodes of the graph represent shape primitives like vectors and quadrilaterals while arcs describing the mutual primitives relations. To be invariant to transformations such as rotation and scaling, relative geometric features extracted from primitives are associated to nodes and edges as attributes. Concerning graph matching, due to the fact of NP-completeness of graph-subgraph isomorphism, a considerable attention is given to different strategies of inexact graph matching. We also present a new scoring function to compute a similarity score between two graphs, using the numerical values associated to the nodes and edges of the graphs. The adaptation of a greedy graph matching algorithm with the new scoring function demonstrates significant performance improvements over traditional exhaustive searches of graph matching.

  • Inexact graph matching
  • graph based representation
  • shape matching

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Université François-Rabelais de Tours, Laboratoire d’Informatique (EA 2101), 64, Avenue Jean Portalis, 37200 Tours, France

Rashid Jalal Qureshi, Jean-Yves Ramel & Hubert Cardot

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Qureshi, R.J., Ramel, JY., Cardot, H. (2007). Graph Based Shapes Representation and Recognition. In: Escolano, F., Vento, M. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2007. Lecture Notes in Computer Science, vol 4538. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72903-7_5

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Automatic Detection and Analysis of Swallowing Sounds in Healthy Subjects and in Patients with Pharyngolaryngeal Cancer

Affiliations.

  • 1 ENT and Head and Neck Surgery, University Hospital of Tours, 2 Boulevard Tonnelé, 37044, Tours, France. [email protected].
  • 2 Service ORL Et Chirurgie Cervico-Faciale, CHU de Tours, 2 Boulevard Tonnelé, 37044, Tours, France. [email protected].
  • 3 Polytech School, University of Tours, 64 Avenue Jean Portalis, 37200, Tours, France.
  • 4 ENT and Head and Neck Surgery, University Hospital of Tours, 2 Boulevard Tonnelé, 37044, Tours, France.
  • 5 Tours Fundamental and Applied Computer Laboratory, University of Tours, CNRS 7002, 64 Avenue Jean Portalis, 37200, Tours, France.
  • 6 Francois-Rabelais University of Tours, University Hospital of Tours, 10 Boulevard Tonnelé, 37032, Tours, France.
  • PMID: 33389178
  • DOI: 10.1007/s00455-020-10225-9

Assessment of swallowing function is often invasive or involves irradiation. Analysis of swallowing sounds is a noninvasive method for assessment of swallowing but is not used in daily medical practice. Dysphagia could be the first symptom that occurs in head and neck cancer. This study evaluated a method for the automatic detection and analysis of swallowing sounds in healthy subjects and in patients with pharyngolaryngeal cancer. A smartphone application, developed for automatic detection and analysis of swallowing sounds was developed and tested in 12 healthy volunteers and in 26 patients with pharyngolaryngeal cancer. Swallowing sounds were recorded with a laryngophone during a standardized meal (100 mL mashed potatoes, 100 mL water, and 100 mL yogurt). Swallowing number and duration were noted; the results were compared to a standard swallowing sound analysis using the software AUDACITY ® . There were no statistically significant differences in swallowing number or duration between the two analysis methods for the three types of foods in healthy volunteers and only for water in patients. In healthy volunteers, the results of our automatic analysis were comparable with those obtained with the standard analysis. However, a better discrimination of swallowing sounds is necessary for the algorithm to obtain reliable results with thicker food in patients with head and neck cancer.

Keywords: Automatic analysis; Automatic detection; Cancer; Deglutition; Deglutition disorders; Swallowing sounds.

© 2021. Springer Science+Business Media, LLC, part of Springer Nature.

Publication types

  • Research Support, Non-U.S. Gov't
  • Deglutition
  • Deglutition Disorders* / diagnosis
  • Deglutition Disorders* / etiology
  • Healthy Volunteers

BDE Polytech Tours

at 64 Avenue Jean de Portalis, Tours , 37200 France

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PEPITE Centre : pôle entrepreneuriat des étudiants de la region Centre Val de Loire Entrepreneurship hub for higher education students in Loire Valley

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    64, Avenue Jean Portalis, 37200 Tours - France {rashid.qureshi,jean-yves.ramel,hubert.cardot}@univ-tours.fr Abstract. In this paper, we propose to represent shapes by graphs. Based on graphic primitives extracted from the binary images, attributed relational graphs were generated. Thus, the nodes of the graph represent shape primitives like

  19. Multicriteria scheduling problems: a survey

    Laboratoire d'Informatique, École d'Ingénieurs en Informatique pour l'Industrie, 64 avenue Jean Portalis, 37200 Tours, France; [email protected].

  20. Quang Chieu Ta

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