The usage of computerised methods in radiological image interpretation is becoming more common. Texture analysis has shown promising results as an image analysis method for detecting non-visible and visible lesions, with a number of applications in magnetic resonance imaging (MRI). Although several recent studies have investigated this topic, there remains a need for further analyses incorporating different clinical materials and taking protocol planning for clinical analyses into account. The purpose of this thesis was to determine the clinical applicability of MRI texture analysis from different viewpoints. This study is based on three patient materials and one collection of healthy athletes and their referents. A total of 220 participants in wider on-going study projects at Tampere University Hospital were included in this thesis. The materials include a study on non-Hodgkin lymphoma, representing soft tissue imaging with malignant disease treatment monitoring; and two studies on central nervous system diseases, mild traumatic brain injury and multiple sclerosis. A musculoskeletal imaging study investigated load-associated physiological changes in healthy participants’ bones. Furthermore, manual Region of Interest (ROI) definition methods and the selection of MRI sequences for analyses of visible and non-visible lesions were evaluated. In summary, this study showed that non-visible lesions and physiological changes as well as visible focal lesions of different aetiologies could be detected and characterised by texture analysis of routine clinical 1.5 T scans. The details of MRI sequence selection and ROI definition in this study may serve as guidelines for the development of clinical protocols. However, these studies are partly experimental and need to be validated with larger sample sizes.Â
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