Biomedical subjects

O Sipilä

Publications and source records attributed to O Sipilä.

6 recordsLinked to original sources

PubMed2004

MRI quality control: six imagers studied using eleven unified image quality parameters.

Quality control of the magnetic resonance imagers of different vendors in the clinical environment is non-harmonised, and comparing the performance is difficult. The purpose of this study was to develop and apply a harmonised long-term quality control protocol for the six imagers in our organisation in order to assure that they fulfil the same basic image quality requirements. The same Eurospin phantom set and identical imaging parameters were used with each imager. Values of 11 comparable parameters describing the image quality were measured. Automatic image analysis software was developed to objectively analyse the images. The results proved that the imagers were operating at a performance level adequate for clinical imaging. Some deficiencies were detected in image uniformity and geometry. The automated analysis of the Eurospin phantom images was successful. The measurements were successfully repeated after 2 weeks on one imager and after half a year on all imagers. As an objective way of examining the image quality, this kind of comparable and objective quality control of different imagers is considered as an essential step towards harmonisation of the clinical MRI studies through a large hospital organisation.

Algorithms↗

PubMed2004

Establishing an international reference image database for research and development in medical image processing.

INTRODUCTION: The lack of comparability of evaluation results is one of the major obstacles of research and development in Medical Image Processing (MIP). The main reason for that is the usage of different image datasets with different quality, size and Gold standard. OBJECTIVES: Therefore, one of the goals of the Working Group on Medical Image Processing of the European Federation for Medical Informatics (EFMI WG MIP) is to develop first parts of a Reference Image Database. METHODS: Kernel of the concept is to identify highly relevant medical problems with significant potential for improvement by MIP, and then to provide respective reference datasets. The EFMI WG MIP has primarily the role of a specifying group and an information broker, while the provider user relationships are defined by bilateral co-operation or license agreements. RESULTS: An explorative database prototype has been implemented using the MySQL database software on the Web. Templates for provider user agreements have been worked out and already applied for own 'pre-RID-MIP' co-operations of the authors. DISCUSSION AND CONCLUSION: First steps towards a comprehensive reference image database have been done. Issues like funding, motivation, management, provision of Gold standards and evaluation guidelines are to be solved. Due to the interest from research groups and industry the efforts will be continued.

Databases as Topic↗

PubMed2000

Transmission imaging for registration of ictal and interictal single-photon emission tomography, magnetic resonance imaging and electroencephalography.

A method developed for registration of ictal and interictal single-photon emission tomography (SPET), magnetic resonance imaging (MRI) and electroencephalography (EEG) is described. For SPET studies, technetium-99m ethyl cysteinate dimer (ECD) was injected intravenously while the patient was monitored on video-EEG to document the ictal or interictal state. Imaging was performed using a triple-head gamma camera equipped with a transmission imaging device using a gadolinium-153 source. The images (128x128 pixels, voxel size 3.7x3.7x3.6 mm3) were reconstructed using an iterative algorithm and postfiltered with a Wiener filter. The gold-plated silver electrodes on the patient's scalp were utilized as markers for registration of the ictal and interictal SPET images, as these metallic markers were clearly seen on the transmission images. Fitting of the marker sets was based on a non-iterative least squares method. The interictal SPET image was subtracted from the ictal image after scaling. The T1-weighted MPRAGE MR images with voxel size of 1.0x1.0x1.0 mm3 were obtained with a 1.5-T scanner. For registration of MR and subtraction SPET images, the external marker set of the ictal SPET study was fitted to the surface of the head segmented from MR images. The SPET registration was tested with a phantom experiment. Registration of ictal and interictal SPET in five patient studies resulted in a 2-mm RMS residual of the marker sets. The estimated RMS error of registration in the final result combining locations of the electrodes, subtraction SPET and MR images was 3-5 mm. In conclusion, transmission imaging can be utilized for an accurate and easily implemented registration procedure for ictal and interictal SPET, MRI and EEG.

Adolescent↗

PubMed1997

Accuracy of a registration procedure for brain SPET and MRI: phantom and simulation studies.

Phantom experiments and simulations were performed to evaluate the significance of different error sources in a clinical registration procedure for brain SPET and MRI based on external markers. The results from the phantom experiments were used to adjust the error model for simulations. In the phantom experiments, 13-14 external markers were attached to the surface of a three-dimensional brain phantom for computing registration. Three internal test markers were used to estimate the accuracy of registration. The phantom was imaged with two different SPET and MRI devices. The mean root-mean-squared (RMS) residual of the locations of the test markers after registration using different combinations of four external markers varied from 3.5 +/- 1.0 to 5.2 +/- 1.3 mm depending on the imaging equipment and parameters used. The accuracy improved with an increasing number of external markers, from 3.2 +/- 0.5 to 4.9 +/- 0.5 mm for 6 markers and from 3.1 +/- 0.1 to 4.7 +/- 0.1 mm for 13 markers. In simulations, the external markers had an error comparable to the corresponding error in the phantom experiments. The error in the test markers was varied independently of that of the external markers. When the locating error of the test markers was removed, about 2 mm of the residuals of the test markers were found to come from this source. When an error comparable to the resolution of the original images (7-10 mm for SPET, 2 mm for MRI) was included in the test markers, the largest mean RMS residual after registration was smaller than the resolution error (8.8 +/- 1.1 mm). This was due to the accuracy of localization of the external markers and the fact that the direction of the error was random for each marker. The size of the registration error of an image volume was site-dependent, being minimal near the centre of mass of the external markers. When comparing the error with the spatial resolution of SPET, it was concluded that the accuracy of registration is not the limiting factor in region-of-interest analysis of registered images, provided that the design and attachment of the marker system are appropriate.

Brain↗

PubMed1996

Registration and display of brain SPECT and MRI using external markers.

Accurate anatomical localisation of abnormalities observed in brain perfusion single-photon emission computed tomography (SPECT) is difficult, but can be improved by correlating data from SPECT and other tomographic imaging modalities. For this purpose we have developed software to register, analyse and display 99mTc-hexamethylpropyleneamine oxime SPECT and 1.0 T MRI of the brain. For registration of SPECT and MRI data external skin markers containing 99mTc (220 kBq) in 50 microliters of coconut butter were used. The software is coded in the C programming language, and the X Window system and the OSF/Motif standards are used for graphics and definition of the user interface. The registration algorithm follows a noniterative least-squares method using singular value decomposition of a 3 x 3 covariance matrix. After registration, the image slices of both data sets are shown at identical tomographic levels. The registration error in phantom studies was on average 4 mm. In the two-dimensional display mode the orthogonal cross-sections of the data sets are displayed side by side. In the three-dimensional mode MRI data are displayed as a surface-shaded 3 D reconstruction and SPECT data as cut planes. The usefulness of this method is demonstrated in patients with cerebral infarcts, brain tumour, herpes simplex encephalitis and epilepsy.

Brain↗

PubMed1995

Segmentation methods for volume determination with 111In/99Tcm SPET.

Objective determination of regions of interest (ROIs) is a prerequisite for the accurate quantification of radionuclide volume distributions in single photon emission tomographic (SPET) images. In this study, we compared four segmentation methods: fixed thresholding (FT), grey level histogram (GL), region growing (RG) and combined region growing and edge detection (RGE). For this purpose, an elliptical phantom containing two cylinders with varying volumes (8-360 ml) and activities of 111In and 99Tcm (2.9-37 kBq ml-1) was employed. Using these methods, the following correlation was observed between true and measured phantom volumes: 111In, r = 0.95 (FT), 0.73 (GL), 0.93 (RG) and 0.92 (RGE); 99Tcm, r = 0.85 (FT), 0.72 (GL), 0.85 (RG) and 0.89 (RGE). Volume determination with FT and RG was not sensitive to the cut-off frequency used in image filtering. A significant correlation was observed between spleen volumes measured with the different segmentation methods, except GL, when applied to the SPET images of 25 patients administered 111In-labelled platelets. On the basis of these results, FT and RG are recommended for the clinical determination of ROIs, although they can be difficult to apply if the signal-to-noise ratio is very low or highly variable, when a combination of different imaging modalities may be the only accurate solution to the segmentation problem. The RGE method can also produce accurate results, but estimation of parameters is laborious with this method. Before being applied clinically, all segmentation methods tested in this study require phantom measurements for the determination of optimal parameters.

Humans↗