OBJECTIVES: Airway dilator muscles play an important role in the analysis of breathing-related symptoms, such as obstructive sleep apnoea. Texture analysis (TA) provides a new non-invasive method for analysing airway dilator muscles. In this study, we propose a TA methodology for airway dilator muscles and prove the robustness of this method. METHODS: 15 orthognathic surgery patients underwent 3-T MRI. Computerized TA was performed on 20 regions of interest (ROIs) in the patients' airway dilator muscles. 53 texture parameters were calculated for all ROIs. The robustness of the TA method was analysed by altering the locations, sizes and shapes of the ROIs. RESULTS: Our study shows that there is significant difference in TA results as the size or shape of ROI changes. The change of location of the ROI inside the studied muscle does not affect the TA results. CONCLUSIONS: The TA method is valid for airway dilator muscles. We propose a methodology in which the number of co-occurrence parameters is reduced by using mean values from four different directions (0°, 45°, 90° and 135°) with pixel spacing of 1 pixel.
OBJECTIVES: Airway dilator muscles play an important role in the analysis of breathing-related symptoms, such as obstructive sleep apnoea. Texture analysis (TA) provides a new non-invasive method for analysing airway dilator muscles. In this study, we propose a TA methodology for airway dilator muscles and prove the robustness of this method. METHODS: 15 orthognathic surgery patients underwent 3-T MRI. Computerized TA was performed on 20 regions of interest (ROIs) in the patients' airway dilator muscles. 53 texture parameters were calculated for all ROIs. The robustness of the TA method was analysed by altering the locations, sizes and shapes of the ROIs. RESULTS: Our study shows that there is significant difference in TA results as the size or shape of ROI changes. The change of location of the ROI inside the studied muscle does not affect the TA results. CONCLUSIONS: The TA method is valid for airway dilator muscles. We propose a methodology in which the number of co-occurrence parameters is reduced by using mean values from four different directions (0°, 45°, 90° and 135°) with pixel spacing of 1 pixel.
Authors: Hui Li; Maryellen L Giger; Zhimin Huo; Olufunmilayo I Olopade; Li Lan; Barbara L Weber; Ioana Bonta Journal: Med Phys Date: 2004-03 Impact factor: 4.071
Authors: Outi M E Alanko; Anna-Liisa Svedström-Oristo; Timo Peltomäki; Tommi Kauko; Martti T Tuomisto Journal: Acta Odontol Scand Date: 2014-05-22 Impact factor: 2.331
Authors: I Kobayashi; A Perry; J Rhymer; B Wuyam; P Hughes; K Murphy; J A Innes; J McIvor; A D Cheesman; A Guz Journal: J Appl Physiol (1985) Date: 1996-05
Authors: W B Van de Graaff; S B Gottfried; J Mitra; E van Lunteren; N S Cherniack; K P Strohl Journal: J Appl Physiol Respir Environ Exerc Physiol Date: 1984-07