CWI develops new algebraic filter for reconstruction of X-Ray images

CWI PhD student Linda Plantagie of the Computational Imaging research group has introduced a new algebraic filter for the use of reconstructing X-Ray images. Linda Plantagie will defend her thesis 13 April at Leiden University.

Publication date: 06-04-2017

CWI PhD student Linda Plantagie of the Computational Imaging research group has introduced a new algebraic filter for the use of reconstructing X-Ray images. A well-known application of reconstructed images is medical imaging with a CT-scanner, and it is also used in industrial and (bio)medical imaging. The filter developed by Plantagie uses algebraic reconstruction methods (ARM’s) that can be used in Filtered Backprojection (a well known reconstruction method). This method enables the reconstruction of images of relatively high quality for few projection angles, limited angular range, or low signal-to-noise ratio. The new algebraic filter improves the accuracy of the computationally efficient FBP method. Linda Plantagie will defend her thesis 13 April at Leiden University.

Look inside an object without destroying it

In many applications, it is useful to look inside an object without destroying it, such as medical examination or product quality assessment in industry. This is possible with a CT-scan, which involves a radiation source and detector which are rotated around the object. This results in several X-ray images with varying angles. A mathematical algorithm uses these two-dimensional images (projections) to create a three-dimensional image of the object’s internal structure. Computed Tomography (CT) is an imaging technique that is used to calculate the interior of an object using X-rays under multiple projection angles. The reconstruction methods can roughly be divided into two categories: analytical reconstruction methods and algebraic reconstruction methods (ARMs).

Filtered backprojection: efficient and accurate

An example of an algorithm from the first category is Filtered Backprojection (FBP). This method has a high computational efficiency and it performs well in cases with many equiangularly distributed projection angles and high signal-to-noise ratio. Is is also highly accurate and easy to implement. ARMs require in general more computation time. They are more robust with respect to noise and can handle few projection angles or a limited angular range better.

In this dissertation, the new algorithm Algebraic filter – Filtered Backprojection (AF-FBP) is introduced, which uses an ARM to create filters that can be used in FBP. The reconstruction quality of AF-FBP approximates that of the corresponding (locally) linear ARM, while the reconstructions are obtained with the computational efficiency of FBP. In cases with a small number of different scanning geometries, using AF-FBP enables the reconstruction of images of relatively high quality for few projection angles, limited angular range, or low signal-to-noise ratio.

What: public defense of Linda Plantagie of her PhD thesis: Algebraic filters for Filtered Backprojection. Promotor: dr. K.J. Batenburg

When: Apr 13, 2017 from 01:45 PM to 03:00 PM

Where: Leiden (Academiegebouw, Rapenburg 73)