Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.656579
Title: Registration and analysis of thermal images in medicine
Author: Izhar, Lila
ISNI:       0000 0004 5348 626X
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2014
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Abstract:
Analyzing and interpreting of thermograms has been increasingly employed in the diagnosis and monitoring of diseases thanks to its non-invasive, non-harmful nature and low cost. This thesis explores methods for thermal image analysis systems based on image registration for two medical applications; skin disease diagnosis and cooling study. In the first application, a novel system is proposed to improve the diagnosis and monitoring of morphoea based on a face sketch and the published lines of Blaschko. In the latter, a novel semi-automated system is proposed to investigate a cooling mask for maxillofacial surgery patients based on thermogram data of normal subjects. In both applications, image registration based on global and local registration methods are found inevitable. A modified normalized gradient cross-correlation (NGC) method to reduce large geometrical differences between two multimodal images of different subjects that are represented by smooth gray edge maps is proposed for the global registration approach. To correct for small displacements between the global outcomes, a simple stochastic based non-rigid affine registration (NRAR) method is proposed. The NRAR method is driven by a cost function that takes into consideration the similarity between two images by a correlation coefficient. A geometric based intensity distortion to ensure only small distortions are accepted, and an overlapping pixel rate are also incorporated. Smooth deformation controlled by an exponential Euclidean based smoothing operator is employed to only edge pixels navigated by a distance function as both the images are represented by edge maps and thus reduces computation time. The NRAR method has shown good performance in correcting for small, varying displacements between images with fairly reliable flexibility and elasticity for both convex and concave objects with the help of the NGC to minimize the initial displacements. A semi-automated approach that includes the NGC and/or the NRAR method followed by determination of cooling area based on the Otsu's thresholding and a seed-based region growing method is found to achieve reliable and reproducible cooling patterns with good correlation with the clinical assessment, for potential cooling study of maxillofacial surgery patients.
Supervisor: Stathaki, Tania Sponsor: Universiti Teknologi PETRONAS
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.656579  DOI: Not available
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