<b>Background:</b> Sport is an important form of physical activity and has been shown to have many health benefits. Cricket is a popular sport in the UK and internationally, but little is known about the short- and long-term health effects of a career in elite cricket. This thesis will describe the long-term physical and mental health of former elite cricketers compared to the general population, explore the association of cricket-related factors with their long-term musculoskeletal health, and evaluate the effect of elite fast bowling on the knee cartilage of current elite fast bowlers. <b>Methods:</b> A sample of male former elite English cricketers was recruited for a cross-sectional retrospective questionnaire study of the long-term health of former cricketers. Chronic conditions in the former cricketers were compared to a general population sample and cricket-related factors including playing position and injury were tested for their association with musculoskeletal outcomes. A sample of male and female current elite fast bowlers was recruited for a biomechanics and cross-sectional MRI study of their knee cartilage. The knee cartilage was compared between the bowlers' trailing leg versus the higher loaded leading leg, and was tested for associations with bowling kinematic and kinetic parameters. <b>Results:</b> The former elite cricketers reported a higher prevalence of osteoarthritis, total hip replacement, total knee replacement, anxiety and depression than the general population sample and a lower prevalence of heart problems than the general population. Injury was the only cricket-related factor analysed to be associated with the musculoskeletal outcomes of joint pain, osteoarthritis, and joint replacement in the former cricketers. The current elite fast bowlers did not demonstrate a statistically significant difference between the compartmental knee cartilage volume in the trailing leg versus the higher loaded leading leg. A clinically significantly greater cartilage volume was found in the lateral tibia compartment of the leading leg than the trailing leg. The lateral tibia cartilage of the leading leg was also found to be significantly associated with the knee flexion/extension moment and abduction/adduction moment at leading leg strike of the bowling action. <b>Conclusions:</b> This research identifies risks and benefits of a career in elite cricket, providing targets for prevention and resource provision for chronic conditions in current cricketers and cricketers transitioning out of elite cricket. These results also suggest that cartilage may be sensitive to bowling loads in current elite fast bowlers, providing evidence that increased physical activity and loading is associated with increased cartilage volume.

Είναι ενδιαφέρουσα αλλά συνάμα δύσκολη η ανάλυση ιατρικών εικόνων, επειδή υπάρχουν πολύ μικρές διακυμάνσεις και μεγάλος όγκος δεδομένων για επεξεργασία. Είναι αρκετά δύσκολο να αναπτυχθεί ένα αυτοματοποιημένο σύστημα αναγνώρισης, το οποίο θα μπορούσε να επεξεργάζεται μεγάλο όγκο πληροφοριών των ασθενών και να παρέχει μια σωστή εκτίμηση. Στην ιατρική, η συμβατική διαγνωστική μέθοδος για εικόνες MR γονάτου για αναγνώριση ανωμαλιών, είναι από την επίβλεψη έμπειρων ιατρών. Η τεχνική της ασαφούς λογικής είναι πιο ακριβής, αλλά αυτό εξαρτάται πλήρως από τη γνώση των εμπειρογνωμόνων, η οποία μπορεί να μην είναι πάντα διαθέσιμη. Στη παρούσα εργασία, τμηματοποιούμε την MR εικόνα του γονάτου με την τεχνική Mean Shift, αναγνωρίζουμε τα κύρια μέρη με τη βοήθεια των ΗΜRF και τέλος εκπαιδεύουμε ταξινομητή ANFIS. Η απόδοση του ταξινομητή ANFIS αξιολογήθηκε όσον αφορά την απόδοση της εκαπαίδευσης και της ακρίβειας ταξινόμησης. Επιβεβαιώθηκε ότι ο ταξινομητής είχε μεγάλη ακρίβεια στην ανίχνευση ανωμαλιών στις ακτινογραφίες Στην εργασία αυτή περιγράφεται η προτεινόμενη στρατηγική για την διάγνωση ανωμαλιών στις εικόνες μαγνητικής τομογραφίας γόνατος. / It is a challenging task to analyze medical images because there are very minute variations & larger data set for analysis. It is a quite difficult to develop an automated recognition system which could process on a large information of patient and provide a correct estimation. The conventional method in medicine for knee MR images classification and diseases detection is by human inspection. Fuzzy logic technique is more accurate but it fully depends on expert knowledge, which may not always available. Here we extract the feature using Mean Shift segmentation and region recognition with HMRF and after that training using the ANFIS tool. The performance of the ANFIS classifier was evaluated in terms of training performance and classification accuracy. Here the result confirmed that the proposed ANFIS classifier with high accuracy in detecting the knee diseases. This work describes the proposed strategy to medical image classification of patient’s MRI scan images of the knee.