19 research outputs found
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Mobile depth sensing technology and algorithms with application to occupational therapy healthcare
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe UK government is striving to shift its current healthcare delivery model from clini-cianâoriented services, to that of patient and selfâcareâoriented intervention strategies. It seeks to do so through Information Communication (ICT) and Computer Mediated Re-ality Technologies (CMRT) as a key strategy to overcome the everâincreasing scarcity of healthcare resources and costs. To this end, in the UK the use of paperâbased information systems have exhibited their limitations in providing apposite care. At the national level, The Royal College of Occupational Therapists (RCOT) identify home visits and modifica-tions as key levers in a multifactorial health programme to evaluate interventions for older people with a history of falling or are identified as being prone to falling. Prescribing Assistive Equipment (AE) is one such mechanism that seeks to reduce the risk of falling whilst promoting the continued independence of physical dexterity and mobility in older adults at home. In the UK, the yearly cost of falls is estimated at ÂŁ2.3 billion. Further evidence places a 30% to 60% abandonment rate on prescribed AE by and large due to a âpoor fitâ and measurement inaccuracies.
To remain aligned with the national strategy, and assist in the eradication of measurement inaccuracies, this thesis employs Mobile Depth Sensing and Motion Track-ing Devices (MDSMTDs) to assist OTs in in the process of digitally measuring the extrin-sic fallârisk factors for the provision of AE. The quintessential component in this assess-ment lies in the measurement of fittings and furniture items in the home. To digitise and aid in this process, the artefact presented in this thesis employs stereo computerâvision and camera calibration algorithms to extract edges in 3D space. It modifies the SobelâFeldman convolution filter by reducing the magnitude response and employs the camera intrinsic parameters as a mechanism to calculate the distortion matrix for interpolation between the edges and the 3D point cloud. Further Augmented Reality User Experience (AR-UX) facets are provided to digitise current state of the art clinical guidance and over-lay its instructions onto the real world (i.e., 3D space).
Empirical mixed methods assessment revealed that in terms of accuracy, the arte-fact exhibited enhanced performance gains over current paperâbased guidance. In terms of accuracy consistency, the artefact can rectify measurement consistency inaccuracies, but there are still a wide range of factors that can influence the integrity of the point-cloud in respect of the deviceâs point-of-view, holding positions and measurement speed. To this end, OTs usability, and adoption preferences materialise in favour of the artefact. In conclusion, this thesis demonstrates that MDSMTDs are a promising alterna-tive to existing paperâbased measurement practices as OTs appear to prefer the digitalâbased system and that they can take measurements more efficiently and accurately
Assessment of perceptual distortion boundary through applying reversible watermarking to brain MR images
The digital medical workflow faces many circumstances in which the images can be manipulated during viewing, extracting and exchanging. Reversible and imperceptible watermarking approaches have the potential to enhance trust within the medical imaging pipeline through ensuring the authenticity and integrity of the images to confirm that the changes can be detected and tracked. This study concentrates on the imperceptibility issue. Unlike reversibility, for which an objective assessment can be easily made, imperceptibility is a factor of human cognition that needs to be evaluated within the human context. By defining a perceptual boundary of detecting the modification, this study enables the formation of objective guidelines for the method of data encoding and level of image/pixel modification that translates to a specific watermark magnitude.
This study implements a relative Visual Grading Analysis (VGA) evaluation of 117 brain MR images (8 original and 109 watermarked), modified by varying techniques and magnitude of image/pixel modification to determine where this perceptual boundary exists and relate the point at which change becomes noticeable to the objective measures of the image fidelity evaluation.
The outcomes of the visual assessment were linked to the images Peak Signal to Noise Ratio (PSNR) values, thereby identifying the visual degradation threshold. The results suggest that, for watermarking applications, if a watermark is applied to the 512x512 pixel (16 bpp grayscale) images used in the study, a subsequent assessment of PSNR=82dB or greater would mean that there would be no reason to suspect that the watermark would be visually detectable.
Keywords: Medical imaging; DICOM; Reversible Watermarking; Imperceptibility; Image Quality; Visual Grading Analysis