Sökning: "Claes Lundström"
Visar resultat 1 - 5 av 8 avhandlingar innehållade orden Claes Lundström.
1. Efficient Medical Volume Visualization : An Approach Based on Domain Knowledge
Sammanfattning : Direct Volume Rendering (DVR) is a visualization technique that has proved to be a very powerful tool in many scientific visualization applications. Diagnostic medical imaging is one domain where DVR could provide clear benefits in terms of unprecedented possibilities for analysis of complex cases and highly efficient work flow for certain routine examinations. LÄS MER
2. Robust Image Registration for Improved Clinical Efficiency : Using Local Structure Analysis and Model-Based Processing
Sammanfattning : Medical imaging plays an increasingly important role in modern healthcare. In medical imaging, it is often relevant to relate different images to each other, something which can prove challenging, since there rarely exists a pre-defined mapping between the pixels in different images. LÄS MER
3. Technology in Absentia : A New Materialist Study of Digital Disengagement
Sammanfattning : The rhetoric associated with society-wide digitalisation promises benefits such as increased quality of life, democracy, or sustainability, which point towards normative trajectories of increased automation and digitalisation of nearly all aspects of society. Meanwhile, there is evidence of a disenchantment with digital use, forming a movement that challenges the pervasiveness of digital artefacts such as the smartphone. LÄS MER
4. Automatic image analysis for decision support in rheumatoid arthritis and osteoporosis
Sammanfattning : Low-energy trauma and fragility fractures represent a major public health problem. The societal cost of the fragility fractures that occurred in Sweden 2010 has been estimated at €4 billion.In rheumatoid arthritis (RA), patient outcomes have improved greatly in recent years. LÄS MER
5. Designing with Machine Learning in Digital Pathology : Augmenting Medical Specialists through Interaction Design
Sammanfattning : Recent advancements in machine learning (ML) have led to a dramatic increase in AI capabilities for medical diagnostic tasks. Despite technical advances, developers of predictive AI models struggle to integrate their work into routine clinical workflows. LÄS MER