Biomedical subjects

G H Bol

Publications and source records attributed to G H Bol.

2 recordsLinked to original sources

PubMed2006

Patient position verification using small IMRT fields.

A commonly used approach to quantify and minimize patient setup errors is by using electronic portal imaging devices (EPIDs). The position of the tumor can be verified indirectly by matching the bony anatomy to a reference image containing the same structures. In this paper we present two off-line methods for detecting the position of the bony anatomy automatically, even if every single portal image of each segment of an IMRT treatment beam contains insufficient matching information. Extra position verification fields will no longer be necessary, which reduces the total dose to the patient. The first method, the stack matching method (SMM), stacks the portal image of each segment of a beam to a three dimensional (3D) volume, and this volume is subsequently used during the matching phase. The second method [the averaged projection matching method (APMM)], is a simplification of the first one, since the initially created volume is reduced again to a 2D artificial image, which speeds up the matching procedure considerably, without a significant loss of accuracy. Matching is based on normalized mutual information. We demonstrate our methods by comparing them to existing matching routines, such as matching based on the largest segment. Both phantom and patient experiments show that our methods are comparable with the results obtained from standard position verification methods. The matches are verified by means of visual inspection. Furthermore, we show that when a distinct area of 40-60 cm2 of the EPID is exposed during one treatment beam, both SMM and APMM are able to deliver a good matching result.

Humans↗

PubMed2005

Assessment of rigid multi-modality image registration consistency using the multiple sub-volume registration (MSR) method.

Registration of different imaging modalities such as CT, MRI, functional MRI (fMRI), positron (PET) and single photon (SPECT) emission tomography is used in many clinical applications. Determining the quality of any automatic registration procedure has been a challenging part because no gold standard is available to evaluate the registration. In this note we present a method, called the 'multiple sub-volume registration' (MSR) method, for assessing the consistency of a rigid registration. This is done by registering sub-images of one data set on the other data set, performing a crude non-rigid registration. By analysing the deviations (local deformations) of the sub-volume registrations from the full registration we get a measure of the consistency of the rigid registration. Registration of 15 data sets which include CT, MR and PET images for brain, head and neck, cervix, prostate and lung was performed utilizing a rigid body registration with normalized mutual information as the similarity measure. The resulting registrations were classified as good or bad by visual inspection. The resulting registrations were also classified using our MSR method. The results of our MSR method agree with the classification obtained from visual inspection for all cases (p < 0.02 based on ANOVA of the good and bad groups). The proposed method is independent of the registration algorithm and similarity measure. It can be used for multi-modality image data sets and different anatomic sites of the patient.

Algorithms↗