A5079388302- Advanced X-ray and CT Imaging
- Acute Ischemic Stroke Management
- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- Advanced X-ray Imaging Techniques
- Radiation Dose and Imaging
- Medical Imaging and Analysis
- Nuclear Physics and Applications
- Traumatic Brain Injury and Neurovascular Disturbances
- Intracerebral and Subarachnoid Hemorrhage Research
University Medical Center Utrecht
2021
Massachusetts General Hospital
2018-2019
University of Twente
2018
Abstract Dual-energy CT (DECT) was introduced to address the inability of conventional single-energy computed tomography (SECT) distinguish materials with similar absorbances but different elemental compositions. However, material decomposition algorithms based purely on physics underlying attenuation process have several limitations, leading low signal-to-noise ratio (SNR) in derived material-specific images. To overcome these, we trained a convolutional neural network (CNN) develop...
Purpose To compare dual-energy CT with iodine quantification to single-energy for evaluation of the spot sign intracranial hematoma expansion. Materials and Methods In this retrospective study, 42 patients (mean age, 66 years ± 15 [standard deviation]; 19 women) were referred assessment hemorrhage from October 2014 January 2017. A machine learning approach (naive Bayes classifier) was used identify markers extravasation risk Specificity sensitivity these then independently validated in 65...
Purpose. To develop a method that enables computed tomography (CT) to magnetic resonance (MR) image registration of complex deformations typically encountered in rotating joints such as the knee joint. Methods. We propose workflow, denoted quaternion interpolated (QIR), consisting three steps, which makes use prior knowledge tissue properties initialise deformable registration. In first step, rigid skeletal components were individually registered. Next, deformation soft was estimated using...