Losing silence, gaining acceptance:A qualitative exploration of the role of thoughts in adult patients with subjective tinnitus

Objective: Tinnitus is one of the most common somatic symptoms to affect humanity. Prevalence rates in adult populations range from 8.2 to 20.1%. Our aim was to understand the beliefs and interpretations of tinnitus and the experience of living with it. Design: An in depth grounded theory interview study. Grounded theory is an inductive approach to developing theory. Sample: Thirteen contrasting people with tinnitus who had sought help from clinical services in England. Results: We identified that the thinking patterns that people held around their tinnitus impacted how they experienced it. A core category emerged from the data, “sense making”. Around “sense making” eight other themes operated. Results are discussed in relation to the literature on tinnitus acceptance and beliefs. Conclusions: The aim of interventions is to foster understanding and enhance perceptions of control, which may minimise the emotional impact of tinnitus and reduce the perceived severity of consequences

Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study

The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively compares the performance of different algorithms to identify vessels in thoracic computed tomography (CT) scans. Vessel segmentation is fundamental in computer aided processing of data generated by 3D imaging modalities. As manual vessel segmentation is prohibitively time consuming, any real world application requires some form of automation. Several approaches exist for automated vessel segmentation, but judging their relative merits is difficult due to a lack of standardized evaluation. We present an annotated reference dataset containing 20 CT scans and propose nine categories to perform a comprehensive evaluation of vessel segmentation algorithms from both academia and industry. Twenty algorithms participated in the VESSEL12 challenge, held at International Symposium on Biomedical Imaging (ISBI) 2012. All results have been published at the VESSEL12 website http://vessel12.grand-challenge.org. The challenge remains ongoing and open to new participants. Our three contributions are: (1) an annotated reference dataset available online for evaluation of new algorithms; (2) a quantitative scoring system for objective comparison of algorithms; and (3) performance analysis of the strengths and weaknesses of the various vessel segmentation methods in the presence of various lung diseases.Rudyanto, RD.; Kerkstra, S.; Van Rikxoort, EM.; Fetita, C.; Brillet, P.; Lefevre, C.; Xue, W.... (2014). Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study. Medical Image Analysis. 18(7):1217-1232. doi:10.1016/j.media.2014.07.003S1217123218

Optical Filters’ Influence on Digital Image Quality in High Temperature Measurements of Surface Properties

This paper is concerned with high temperature image quantitative analysis systems. Particular attention is paid to computerised system for surface properties (wetting angle and surface tension) determination. A brief description of the system is given. The specificity of the performed measurements based on images presenting heat-emitting objects is considered. Moreover, the significance of optical filters’ usage is explained. Infrared and neutral density filters are regarded. Influence of these filters on digital image quality is deliberated. Especially image noise presence is considered. The detailed analysis of noise properties change due filters usage is carried out. Finally, results of the analysis are presented and discussed

Optimal Selection of Image Segmentation Algorithm for Heat-Emitting Objects

In this paper problem of image segmentation quality is delibered. Especially, issue of segmentation method selection for images presenting heat-emitting objects is discussed. Particular attention is paid to thresholding method and edge-based image segmentation. Results of applying these methods to exemplary images are presented and discussed