Biomedical subjects

L G Nyúl

Publications and source records attributed to L G Nyúl.

6 recordsLinked to original sources

PubMed2003

[3D cross section of the laryngotracheal tract. A new method for visualization and quantification of tracheal stenoses].

PURPOSE: Demonstration of a technique for 3D assessment of tracheal stenoses, regarding site, length and degree, based on spiral computed tomography (S-CT). PATIENTS AND METHODS: S-CT scanning and automated segmentation of the laryngo-tracheal tract (LTT) was followed by the extraction of the LTT medial axis using a skeletonisation algorithm. Orthogonal to the medial axis the LTT 3D cross sectional profile was computed and presented as line charts, where degree and length were obtained. Values for both parameters were compared between 36 patients and 18 normal controls separately. Accuracy and precision was derived from 17 phantom studies. RESULTS: Average degree and length of tracheal stenoses were found to be 60.5% and 4.32 cm in patients compared to minor caliber changes of 8.8% and 2.31 cm in normal controls (p <0.005). For the phantoms an excellent correlation between the true and computed 3D cross sectional profile was found (p <0.005) and an accuracy for length and degree measurements of 2.14 mm and 2.53% respectively could be determined. The corresponding figures for the precision were found to be 0.92 mm and 2.56%. CONCLUSION: LTT 3D cross sectional profiles permit objective, accurate and precise assessment of LTT caliber changes. Minor LTT caliber changes can be observed even in normals and, in case of an otherwise normal S-CT study, can be regarded as artefacts.

Adolescent↗

PubMed2001

Multiprotocol MR image segmentation in multiple sclerosis: experience with over 1,000 studies.

RATIONALE AND OBJECTIVES: Multiple sclerosis (MS) is an acquired disease of the central nervous system. Several clinical measures are commonly used to express the severity of the disease, including the Expanded Disability Status Scale and the ambulation index. These measures are subjective and may be difficult to reproduce. The aim of this research is to investigate the possibility of developing more objective measures derived from MR imaging. MATERIALS AND METHODS: Various magnetic resonance (MR) imaging protocols are being investigated for the study of MS. Seeking to replace the Expanded Disability Status Scale and ambulation index with an objective means to assess the natural course of the disease and its response to therapy, the authors have developed multiprotocol MR image segmentation methods based on fuzzy connectedness to quantify both macrosopic features of the disease (lesions, gray matter, white matter, cerebrospinal fluid, and brain parenchyma) and the microscopic appearance of diseased white matter. Over 1,000 studies have been processed to date. RESULTS: By far the strongest correlations with the clinical measures were demonstrated by the magnetization transfer ratio histogram parameters obtained for the various segmented tissue regions. These findings emphasize the importance of considering the microscopic and diffuse nature of the disease in the individual tissue regions. Brain parenchymal volume also demonstrated a strong correlation with clinical measures, which suggests that brain atrophy is an important disease indicator. CONCLUSION: Fuzzy connectedness is a viable, highly reproducible segmentation method for studying MS.

Humans↗

PubMed2001

Brain atrophy in relapsing-remitting multiple sclerosis: fractional volumetric analysis of gray matter and white matter.

PURPOSE: To determine the fractional brain tissue volume changes in the gray matter and white matter of patients with relapsing-remitting multiple sclerosis (MS) and to correlate these measurements with clinical disability and total lesion load. MATERIALS AND METHODS: Thirty patients with relapsing-remitting MS and 25 healthy control subjects underwent magnetic resonance imaging. Fractional brain tissue volumes (tissue volume relative to total intracranial volume) were obtained from the total segmented gray matter and white matter in each group and were analyzed. RESULTS: The fractional volume of white matter versus that of gray matter was significantly lower (-6.4%) in patients with MS (P <.0001) than in control subjects. Neither gray matter nor white matter fractional volume measurements correlated with clinical disability in the patients with MS. CONCLUSION: Loss of brain parenchymal volume in patients with relapsing-remitting MS is predominantly confined to white matter. Analysis of fractional brain tissue volumes provides additional information useful in characterizing MS and may have potential in evaluating treatment strategies.

Adult↗

PubMed2000

Numerical tissue characterization in MS via standardization of the MR image intensity scale.

Image intensity standardization is a recently developed postprocessing method that is capable of correcting the signal intensity variations in MR images. We evaluated signal intensity of healthy and diseased tissues in 10 multiple sclerosis (MS) patients based on standardized dual fast spin-echo MR images using a numerical postprocessing technique. The main idea of this technique is to deform the volume image histogram of each study to match a standard histogram and to utilize the resulting transformation to map the image intensities into standard scale. Upon standardization, the coefficients of variation of signal intensities for each segmented tissue (gray matter, white matter, lesion plaques, and diffuse abnormal white matter) in all patients were significantly smaller (2.3-9.2 times) than in the original images, and the same tissues from different patients looked alike, with similar intensity characteristics. Numerical tissue characterizability of different tissues in MS achieved by standardization offers a fixed tissue-specific meaning for the numerical values and can significantly facilitate image segmentation and analysis.

Adult↗

PubMed2000

New variants of a method of MRI scale standardization.

One of the major drawbacks of magnetic resonance imaging (MRI) has been the lack of a standard and quantifiable interpretation of image intensities. Unlike in other modalities, such as X-ray computerized tomography, MR images taken for the same patient on the same scanner at different times may appear different from each other due to a variety of scanner-dependent variations and, therefore, the absolute intensity values do not have a fixed meaning. We have devised a two-step method wherein all images (independent of patients and the specific brand of the MR scanner used) can be transformed in such a way that for the same protocol and body region, in the transformed images similar intensities will have similar tissue meaning. Standardized images can be displayed with fixed windows without the need of per-case adjustment. More importantly, extraction of quantitative information about healthy organs or about abnormalities can be considerably simplified. This paper introduces and compares new variants of this standardizing method that can help to overcome some of the problems with the original method.

Algorithms↗

PubMed1999

On standardizing the MR image intensity scale.

The lack of a standard image intensity scale in MRI causes many difficulties in image display and analysis. A two-step postprocessing method is proposed for standardizing the intensity scale in such a way that for the same MR protocol and body region, similar intensities will have similar tissue meaning. In the first step, the parameters of the standardizing transformation are "learned" from a set of images. In the second step, for each MR study these parameters are used to map their histogram into the standardized histogram. The method was tested quantitatively on 90 whole-brain studies of multiple sclerosis patients for several protocols and qualitatively for several other protocols and body regions. Measurements using mean squared difference showed that the standardized image intensities have statistically significantly (P < 0.01) more consistent range and meaning than the originals. Fixed gray level windows can be established for the standardized images and used for display without the need of per case adjustment. Preliminary results also indicate that the method facilitates improving the degree of automation of image segmentation. Magn Reson Med 42:1072-1081, 1999.

Algorithms↗