The department of Imaging Physics develops novel instrumentation and imaging technologies. We are driven by our scientific curiosity and problem oriented nature in research with a strong connection to industry and to educate future leaders in the field of imaging science.
The scientific staff of the department is formed by independent Principle Investigators or Educators.
04 May 2017
Richard Faasse started his BSc project
Richard works on a Monte Carlo diffusion simulation to simulate the diffusion-weighted MRI signal of a brain phantom. His supervisors are Frans Vos & Joor Arkesteijn
03 May 2017
Luuk Balkenende started his BSc project
Luuk started his BSc thesis on: "Optimum Metric for 20 Datafusion in localization microsopy". His supervisor is Sjoerd Stallinga.
From light spots to supersharp images
Making detailed 3D images of proteins in living cells with a special light microscope, without damaging those cells. That is what Sjoerd Stallinga, winner of an ERC Advanced grant worth 2.3 million euros, wants to achieve. In order to do so he is going to scan samples nanometer by nanometer using a sophisticated 3D light pattern in an approach that requires extensive collaboration between different disciplines.
Spotlight on aggressive cancer cells
Metastases in cancer are often caused by a few abnormal cells. These behave more aggressively than the other cancer cells in a tumour. Miao-Ping Chien and Daan Brinks are working together, from two different universities, on a method to detect these cells. Their research has now been published in Nature Biomedical Engineering
How to find structurally different molecules before they disappear in the average?
Particle fusion for single molecule localization microscopy improves signal-to-noise ratio and overcomes underlabeling, but ignores structural heterogeneity or conformational variability. This study presents a-priori knowledge-free unsupervised classification of structurally different particles employing the Bhattacharya cost function as dissimilarity metric.
The impact of noise on Structured Illumination Microscopy image reconstructions
Super-resolution structured illumination microscopy (SIM) has become a widely used method for biological imaging. Standard reconstruction algorithms, however, are prone to generate noise-specific artifacts that limit their applicability for lower signal-to-noise data. Here we present a physically realistic noise model that explains the structured noise artifact, which we then use to motivate new complementary reconstruction approaches.
A new tool to understand the brain
How does our brain work? An international team of researchers, including lead author Daan Brinks of TU Delft, has taken another step towards answering that question. They have created a new tool that allows them to image electrical signals in brains with an unprecedented combination of precision, resolution, sensitivity, and depth.
Researchers make 3D image with light microscope
For the first time, Delft researchers have succeeded in making a three-dimensional image of a cellular component using light. The component in question is the nuclear pore complex: tunnels that facilitate traffic to and from the cell nucleus. Studying cell components in 3D can help to determine the cause of various diseases, among other things. The researchers have published their findings in Nature Communications.
Decoding movement intentions in the brain using ultrasound waves
While many techniques can image brain activity, this was the first time that a new technology, called functional ultrasound imaging, was used to detect motor planning deep within the brain. The team is now applying functional ultrasound decoding to more complicated motor control tasks. At ImPhys, Dr. Maresca is developing ultrasound technologies to image brain activity down to the cellular scale.