Key research themes
1. How can the technical quality and image layer of panoramic radiographs be quantitatively evaluated and improved for clinical reliability?
This research area focuses on assessing and enhancing the clinical image quality of panoramic radiographs, which is crucial for accurate diagnosis in dental and maxillofacial applications. Evaluations cover error types affecting image quality, objective scoring of images using clinical evaluation charts, and the design of phantoms replicating mandibular anatomy for precise assessment of focal trough (image layer). Improving image quality assurance supports better diagnostic outcomes and helps establish standardized guidelines for imaging protocols.
2. How can advanced imaging reconstruction techniques from CBCT data enhance panoramic radiograph quality and diagnostic utility especially in artifact-prone conditions?
This area investigates computational methods to reconstruct panoramic radiographs from volumetric cone beam computed tomography (CBCT) data, addressing traditional panoramic scan limitations (e.g., out-of-focus blur, additional radiation dose). The focus lies on automated dental arch detection, arch curve fitting, and projection data extraction to synthesize panoramic images with higher completeness and contrast, reducing metal implant artifacts. These methods aim to improve diagnostic robustness and streamline workflow by leveraging CBCT-derived data.
3. What roles do immersive visualization technologies play in improving radiological image interpretation and training?
This theme encompasses the development and evaluation of immersive technologies such as virtual reality (VR) and augmented reality (AR) to enhance radiology education, diagnostics, and training. It investigates human factors impacting image perception in traditional reading room environments, prototypes HMD-based visualization and interaction platforms to mitigate ergonomic and ambient interference, and evaluates usability and efficacy in clinical or educational contexts. This research leverages spatial visualization and interaction affordances to augment user presence, comprehension, and diagnostic accuracy.