Digital Image Processing for Clinical Research
We have access to a wide range of fantastic (AI) tools, developed by our own researchers. With the help of our experienced research software engineers, we can reuse these for new clinical applications.
In this section we provide you with some examples of digital image processing that can be performed, organized per body part. This list is not extensive and is growing every day, so don’t hesitate to contact us if your specific tool is not listed below!
- Automatic organ segmentation on CT (see figure below)
- Automatic organ segmentation on MRI (see figure below)
- Automatic organ segmentation on a variety of modalities
- Minimally interactive soft-tissue tumor segmentation on MRI or CT
- Automatic tumor segmentation (and morphology measures, e.g. RECIST) on a variety of modalities
- Automatic radiomics analysis to develop prediction models on different modalities
- Automatic tumor quantification (e.g. diagnosis) using previously developed radiomics model (e.g. liver, soft tissue, rectal tumors) on MRI or CT
- Super-resolution method for multi-slice MRI
- Automatic registration for a variety of applications
Organs that can be automatically segmented on a CT scan using Totalsegmentator.
Organs that can be automatically segmented on an MRI scan using Totalsegmentator.
- Automatic brain (region) segmentation/volume on MRI
- Analysis of white matter tracts on brain diffusion MRI
- Arterial spin labelling (ASL) quantification on brain MRI
- White matter hyper intensities segmentation on brain MRI
- Automatic labelling of MRI scans to T1, T1C, T2, PD and derived maps
- Automatic glioma segmentation on MRI
- Multi-parametric analysis of the brain on (advanced) (PET-)MRI sequences
- Collateral scoring for stroke patients on CTA
- Brain vessel segmentation on CTA
- Automatic TICI scoring for stroke patients on DSA
- Brain atlas probability maps
- Automatic bone age assessment on hand DXA scans
- Comprehensive knee (structures) segmentation on MRI
- Comprehensive hip (structures) segmentation on MRI
- Different biomarkers for a variety of hip disorders on MRI
(Collaboration with) other departments
The field of medical imaging is not restricted to the department of Radiology & Nuclear Medicine alone. Think of automatic 3D photocephalometric measurements of the skull for neurosurgery and skin cancer risk assessment on regular photography for dermatology. In ophthalmology there is for example automatic segmentation of cone photoreceptors in AO-FIO images, automatic endothelial cell counting, and a variety of manual and AI-assisted grading options for retinal imaging for quantification of disease burden (e.g. AMD) and morphology (e.g. vasculature, retinal layers) provided by the EyeNED Reading Center. In pulmonology, a variety of (semi-)automatic airway measurements and quantification of several structural lung diseases (e.g. CF, BPD) can be performed on lung CT scans by our colleagues from LungAnalysis. From an epidemiologic perspective, it is beneficial to use software to harmonize measurements for a very large number of study subjects, for example when measuring carotid and vertebrobasilar artery calcifications on CT scans. Finally, you could integrate for example pathology images in automatic diagnosis pipelines originally based on radiological images only.
Does one of these examples spark your interest? Don’t hesitate to contact the Imaging Office and we would be very happy to bring you in contact with the people involved!
Does one of these examples spark your interest? Don’t hesitate to contact the Imaging Office and we would be very happy to bring you in contact with the people involved!