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J Dengler

Publications and source records attributed to J Dengler.

8 recordsLinked to original sources
PubMed1997

An automated registration algorithm for measuring MRI subcortical brain structures.

An automated registration algorithm was used to elastically match an anatomical magnetic resonance (MR) atlas onto individual brain MR images. Our goal was to evaluate the accuracy of this procedure for measuring the volume of MRI brain structures. We applied two successive algorithms to a series of 28 MR brain images, from 14 schizophrenia patients and 14 normal controls. First, we used an automated segmentation program to differentiate between white matter, cortical and subcortical gray matter, and cerebrospinal fluid. Next, we elastically deformed the atlas segmentation to fit the subject's brain, by matching the white matter and subcortical gray matter surfaces. To assess the accuracy of these measurements, we compared, on all 28 images, 11 brain structures, measured with elastic matching, with the same structures traced manually on MRI scans. The similarity between the measurements (the relative difference between the manual and the automated volume) was 97% for whole white matter, 92% for whole gray matter, and on average 89% for subcortical structures. The relative spatial overlap between the manual and the automated volumes was 97% for whole white matter, 92% for whole gray matter, and on average 75% for subcortical structures. For all pairs of structures rendered with the automated and the manual method, Pearson correlations were between r = 0.78 and r = 0.98 (P < 0.01, N = 28), except for globus pallidus, where r = 0.55 (left) and r = 0. 44 (right) (P < 0.01, N = 28). In the schizophrenia group, compared to the controls, we found a 16.7% increase in MRI volume for the basal ganglia (i.e., caudate nucleus, putamen, and globus pallidus), but no difference in total gray/white matter volume or in thalamic MR volume. This finding reproduces previously reported results, obtained in the same patient population with manually drawn structures, and suggests the utility/efficacy of our automated registration algorithm over more labor-intensive manual tracings.

Adolescent↗
PubMed1995

Automatic identification of gray matter structures from MRI to improve the segmentation of white matter lesions.

The segmentation of MRI scans of patients with white matter lesions (WML) is difficult because the MRI characteristics of WML are similar to those of gray matter. Intensity-based statistical classification techniques misclassify some WML as gray matter and some gray matter as WML. We developed a fast elastic matching algorithm that warps a reference data set containing information about the location of the gray matter into the approximate shape of the patient's brain. The region of white matter was segmented after segmenting the cortex and deep gray matter structures. The cortex was identified by using a three-dimensional, region-growing algorithm that was constrained by anatomical, intensity gradient, and tissue class parameters. White matter and WML were then segmented without interference from gray matter by using a two-class minimum-distance classifier. Analysis of double-echo spin-echo MRI scans of 16 patients with clinically determined multiple sclerosis (MS) was carried out. The segmentation of the cortex and deep gray matter structures provided anatomical context. This was found to improve the segmentation of MS lesions by allowing correct classification of the white matter region despite the overlapping tissue class distributions of gray matter and MS lesion.

Algorithms↗
PubMed1990

Differential screening of murine ascites cDNA libraries by means of in vitro transcripts of cell-cycle-phase-specific cDNA and digital image processing.

Cell-cycle-phase-specific cDNA libraries were prepared in the lambda gt10 vector and in the in vitro transcription vector, pBluescript. Plaques of the cDNA libraries prepared in the lambda gt10 vector were differentially screened with (a) in vitro transcripts of the cell-cycle-phase-specific cDNAs cloned in the transcription vector and (b) with first-strand cDNA of mRNA from phase-synchronous cells. The results suggest that first-strand cDNA can be replaced, at least in prescreening experiments, by in vitro transcripts of representative cDNA libraries prepared in in vitro transcription vectors. The fractions of differential clones detected with in vitro transcripts (1.2%) and with first-strand cDNA (1%) were in the same order. Individual clones selected by differential hybridization with in vitro transcripts could be verified by differential hybridization with cell-cycle-phase-specific first-strand cDNA. This indicates that the pattern of stage-specific prevalences of cDNA clones is essentially retained during careful amplifications of large cDNA libraries. The application of in vitro transcripts of stage-specific cDNA for differential screening experiments is of interest in cases where the amount of biological material is either limited or difficult to prepare. It also allows standardization of the probes in repeated screening experiments. Three clones reflecting cell-cycle-phase-specific mRNA prevalences were chosen and analyzed on the sequence level. Two sequences with S-phase prevalences were identified. They code for elongation factor EF1 alpha and for glyceraldehyde-3-phosphate dehydrogenase, respectively. The third sequence reflects the first cDNA of a mRNA with significant prevalence in G2-phase cells.(ABSTRACT TRUNCATED AT 250 WORDS)

Amino Acid Sequence↗
PubMed1988

[Film digital and texture analysis for digital classification of pulmonary spot opacities].

The study aimed at evaluating the effect of different methods of digitisation of radiographic films on the digital classification of pulmonary opacities. Test sets from the standard of the International Labour Office (ILO) Classification of Radiographs of Pneumoconiosis were prepared by film digitisation using a scanning microdensitometer or a video digitiser based on a personal computer equipped with a real time digitiser board and a vidicon or a Charge Coupled Device (CCD) camera. Seven different algorithms were used for texture analysis resulting in 16 texture parameters for each region. All methods used for texture analysis were independent of the mean grey value level and the size of the image analysed. Classification was performed by discriminant analysis using the classes from the ILO classification. A hit ratio of at least 85% was achieved for a digitisation by scanner digitisation or the vidicon, while the corresponding results of the CCD camera were significantly less good. Classification by texture analysis of opacities of chest X-rays of pneumoconiosis digitised by a personal computer based video digitiser and a vidicon are of equal quality compared to digitisation by a scanning microdensitometer. Correct classification of 90% was achieved via the discribed statistical approach.

Algorithms↗
PubMed1987

[Classification of spot-shaped lung changes by texture analysis].

Classification of opacities in pneumoconiosis was accomplished by textural analysis in digitised chest x-rays. A good discrimination was achieved by a set of 10 parameters. These texture measures were computed by algorithms for edge detection, local extremes, difference statistics, the co-occurrence matrix and the power spectrum. The classes of the training set were classified correctly at 99%. A test set comprising additional classes that were not contained in the training set, was classified at 82%.

Algorithms↗
PubMed1986

[Multilevel structure isolation using modules based on the example of thoracic radiography].

Conventional chest radiographs were digitized and processed by multilevel band pass filtering. By this procedure different structural components are isolated according to their local spatial frequencies. In chest radiographs a textural component can be separated from a skeletal component. Evaluation of radiological images is facilitated because changes can be looked for at relevant levels. A reconstruction of the image is possible, using different weighting factors to enhance interesting structural components.

Humans↗