Radiation therapy has been successful in treating lung cancer patients, but its efficacy is limited by the inability to account for the respiratory motion during treatment planning and radiation dose delivery. Physics-based lung deformation models facilitate the motion computation of both tumor and local lung tissue during radiation therapy. In this dissertation, a novel method is discussed to accurately register 3D lungs across the respiratory phases from 4D-CT datasets, which facilitates the estimation of the volumetric lung deformation models. This method uses multi-level and multi-resolution optical flow registration coupled with thin plate splines (TPS), to address registration issue of inconsistent intensity across respiratory phases. It achieves higher accuracy as compared to multi-resolution optical flow registration and other commonly used registration methods. Results of validation show that the lung registration is computed with 3 mm Target Registration Error (TRE) and approximately 3 mm Inverse Consistency Error (ICE). This registration method is further implemented in GPU based real time dose delivery simulation to assist radiation therapy planning.

Most previous research has explored how words are processed in isolation. However, reading is a complex process where an interplay of various factors affects word identification. Moreover, previous research has mainly focused on alphabetical languages, so extension of the existent findings to non-alphabetical languages is crucial. The current dissertation uses natural reading paradigms to study eye-movements and neurophysiological correlates of the statistical properties of words that affect word recognition during natural reading in English and Chinese. Chapter 2 concerns the time-courses of word frequency and semantic similarity effects in the reading of English derived words. Previous research pointed to a paradox where behavioural experimental techniques showed earlier signatures of these properties than neuro-imaging techniques. By combining eye-tracking and EEG and applying analytical techniques that target the onset of these effects, this study aims at investigating this paradox. Results still show that neurophysiological responses are either largely absent or appear at the same time as shown in eye-movement data. Chapter 3 shows that the existence of spelling errors negatively impacts the recognition of correct spellings in Chinese. This is revealed by the “spelling entropy effect”, which measures the uncertainty about choosing between correct and alternative spelling variants. This is the first study that used co-registration of eye-tracking and EEG to explore the behavioral and neurophysiological signatures of this uncertainty. Chapter 4 studies how segmentation probabilities influence word segmentation and identification when reading Chinese. The results reveal that space becomes beneficial only when located at places where segmentation probability is considered high. This study is among the first to show beneficial effects of spacing at the sentence level and demonstrates how segmentation probabilities play a crucial role in Chinese word segmentation. Cumulatively, the results obtained point to the existence of numerous factors involved in word identification in both alphabetic and logographic languages, which should be explored using natural reading experimental paradigms, such as co-registration of EEG and eye-tracking, for obtaining a multifaceted view of word recognition processes. / Thesis / Doctor of Philosophy (PhD)

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