Achim Knepper

Somatotopy of human hand somatosensory cortex revealed by dipole source analysis of early somatosensory evoked potentials and 3D-NMR tomography

Somatosensory evoked potentials (SEPs) to median nerve and finger stimulation were analyzed by means of spatio-temporal dipole modelling combined with 3D-NMR tomography in 8 normal subjects. The early SEPs were modelled by 3 equivalent dipoles located in the region of the brain-stem (B) and in the region of the contralateral somatosensory cortex (T and R). Dipole B explained peaks P14 and N18 at the scalp. Dipole T was tangentially oriented and explained the N20-P20, dipole R was radially oriented and modelled the P22. The tangential dipole sources T were located within a distance of 6 mm on the average and all were less than 9 mm from the posterior bank of the central sulcus. In 6 subjects the tangential sources related to finger stimulation arranged along the central sulcus according to the known somatotopy. The radial sources did not show a consistent somatotopic alignment across subjects. We conclude that the combination of dipole source analysis and 3D-NMR tomography is a useful tool for functional localization within the human hand somatosensory cortex.

Source analysis of median nerve and finger stimulated somatosensory evoked potentials: Multichannel simultaneous recording of electric and magnetic fields combined with 3d-MR tomography

SummaryAt the current state of technology, multichannel simultaneous recording of combined electric potentials and magnetic fields should constitute the most powerful tool for separation and localization of focal brain activity. We performed an explorative study of multichannel simultaneous electric SEPs and magnetically recorded SEFs. MEG only sees tangentially oriented sources, while EEG signals include the entire activity of the brain. These characteristics were found to be very useful in separating multiple sources with overlap of activity in time. The electrically recorded SEPs were adequately modelled by three equivalent dipoles located: (1) in the region of the brainstem, modelling the P14 peak at the scalp, (2) a tangentially oriented dipole, modelling the N20-P20 and N30-P30 peaks, and part of the P45, and (3) a radially oriented dipole, modelling the P22 peak and part of the P45, both located in the region of the somatosensory cortex. Magnetically recorded SEFs were adequately modelled by a single equivalent dipole, modelling the N20-P20 and N30-P30 peaks, located close to the posterior bank of the central sulcus, in area 3b (mean deviation: 3 mm). The tangential sources in the electrical data were located 6 mm on average from the area 3b. MEG and EEG was able to locate the sources of finger stimulated SEFs in accordance with the somatotopic arrangement along the central fissure. A combined analysis demonstrated that MEG can provide constraints to the orientation and location of sources and helps to stabilize the inverse solution in a multiple-source model of the EEG.

Navigation Support for Surgery by Means of Optical Position Detection

In an interdisciplinary research project a “navigation” support for scull base surgery has been developed. By combining 3D position measurement techniques, digital image processing and 3D display techniques the spatial position and orientation of an operating instrument is being visualized on a display, which shows a CT-generated view of the operation area.

Computer-assisted Diagnosis for Early Stage Pleural Mesothelioma: Towards Automated Detection and Quantitative Assessment of Pleural Thickenings from Thoracic CT Images

OBJECTIVES Pleural thickenings as biomarker of exposure to asbestos may evolve into malignant pleural mesothelioma. For its early stage, pleurectomy with perioperative treatment can reduce morbidity and mortality. The diagnosis is based on a visual investigation of CT images, which is a time-consuming and subjective procedure. Our aim is to develop an automatic image processing approach to detect and quantitatively assess pleural thickenings. METHODS We first segment the lung areas, and identify the pleural contours. A convexity model is then used together with a Hounsfield unit threshold to detect pleural thickenings. The assessment of the detected pleural thickenings is based on a spline-based model of the healthy pleura. RESULTS Tests were carried out on 14 data sets from three patients. In all cases, pleural contours were reliably identified, and pleural thickenings detected. PC-based Computation times were 85 min for a data set of 716 slices, 35 min for 401 slices, and 4 min for 75 slices, resulting in an average computation time of about 5.2 s per slice. Visualizations of pleurae and detected thickenings were provided. CONCLUSION Results obtained so far indicate that our approach is able to assist physicians in the tedious task of finding and quantifying pleural thickenings in CT data. In the next step, our system will undergo an evaluation in a clinical test setting using routine CT data to quantify its performance.

Detection and follow-up assessment of pleural thickenings from 3D CT data

Pleural thickenings as biomarker of exposure to asbestos may evolve into malignant pleural mesothelioma. The diagnosis is based on a visual investigation of CT images, which is a time consuming and subjective procedure. Our image processing system segments the lung areas, and identifies the pleural contours using thresholding and contour relaxation. A convexity model is then used together with a Hounsfield unit threshold to detect pleural thickenings. The assessment of the detected pleural thickenings is based on a spline-based model of the healthy pleura. Follow-up study between two consecutive data, carried out by normalizing the coordinate system, leads to a diagnosis supporting tool to detect pleural mesothelioma in its early stage.

An approach to segment lung pleura from CT data with high precision

A new approach to segment pleurae from CT data with high precision is introduced. This approach is developed in the segmentations framework of an image analysis system to automatically detect pleural thickenings. The new technique to carry out the 3D segmentation of lung pleura is based on supervised range-constrained thresholding and a Gibbs-Markov random field model. An initial segmentation is done using the 3D histogram by supervised range-constrained thresholding. 3D connected component labelling is then applied to find the thorax. In order to detect and remove trachea and bronchi therein, the 3D histogram of connected pulmonary organs is modelled as a finite mixture of Gaussian distributions. Parameters are estimated using the Expectation-Maximization algorithm, which leads to the classification of that pulmonary region. As consequence left and right lungs are separated. Finally we apply a Gibbs-Markov random field model to our initial segmentation in order to achieve a high accuracy segmentation of lung pleura. The Gibbs- Markov random field is combined with maximum a posteriori estimation to estimate optimal pleural contours. With these procedures, a new segmentation strategy is developed in order to improve the reliability and accuracy of the detection of pleural contours and to achieve a better assessment performance of pleural thickenings.

3D-Erkennung, Analyse und Visualisierung pleuraler Verdickungen in CT-Daten

Aufbauend auf fruheren Arbeiten wurde ein Bildverarbeitungssystem entwickelt, welches pleurale Verdickungen automatisch lokalisiert und visualisiert. Es liefert reproduzierbare, quantitative Daten, die eine genauere Beobachtung der Verdickungen ermoglichen als die konventionelle Befundungsmethode, und reduziert den fur die Befundung notigen Zeitaufwand. Die automatische Detektion findet innerhalb eines zweistufigen Algorithmus statt, der zuerst aus allen Schichten des Datensatzes die Pleurakonturen extrahiert und darauf aufbauend die Verdickungen in den Pleurakonturen detektiert. Da die Anderung der Form einer Verdickung ein wichtiges Kriterium bei der Entscheidung ist, ob eine Verdickung entartet, wurde eine Moglichkeit zur Visualisierung der Verdickungen und der Lungenflugel implementiert. Diese konnen nun aus allen Perspektiven betrachtet werden. Unterschiede in den Verdickungen zweier aufeinanderfolgender Scans konnen so erkannt werden.

Automatic calibration of a scanner-based laser welding system

In precision engineering scanners are widely used for laser beam positioning. Equipped with cameras, scanners enable process monitoring or even position recognition of the parts to be welded.To allow precise welding or position recognition, it is essential to calibrate a welding system. Instead of calibrating the whole system, most approaches only help to adjust the laser beam position. Consequently, the varying lateral offset between the laser’s focus point and the camera’s field of view, due to chromatic aberration of the scanner optics, cannot be compensated. Furthermore, these approaches require manual microscopic measurement of weld seams, which comes along with several downsides.This paper proposes two techniques for automatic calibration without these downsides by use of the system-incorporated camera. The first technique is the calibration at laser wavelength. To this end, the system automatically creates laser spots, evaluates their positions and possible offsets and finally fits an affine model for compensation. The second technique is based on a specially coded test pattern, which is used for calibration at camera wavelengths.Experimental results confirm the accuracy of the calibration obtained.In precision engineering scanners are widely used for laser beam positioning. Equipped with cameras, scanners enable process monitoring or even position recognition of the parts to be welded.To allow precise welding or position recognition, it is essential to calibrate a welding system. Instead of calibrating the whole system, most approaches only help to adjust the laser beam position. Consequently, the varying lateral offset between the laser’s focus point and the camera’s field of view, due to chromatic aberration of the scanner optics, cannot be compensated. Furthermore, these approaches require manual microscopic measurement of weld seams, which comes along with several downsides.This paper proposes two techniques for automatic calibration without these downsides by use of the system-incorporated camera. The first technique is the calibration at laser wavelength. To this end, the system automatically creates laser spots, evaluates their positions and possible offsets and finally fits an affine model ...

MEG- und EEG-Methodenvergleich am Beispiel der N. medianus SEP

Zur Zeit gibt es eine sehr kontroverse Diskussion uber den Wert des MEG im Vergleich zum EEG, ausgelost durch eine vergleichende Untersuchung von Cohen et al. (1990). Diese Diskussion fokussiert auf die Lokalisationsgenauigkeit mit beiden Methoden und vernachlassigt gravierende prinzipielle Unterschiede zwischen beiden. Aus theoretischen Studien und Uberlegungen ist seit langem bekannt, das die MEG nur tangential orientierte und oberflachennahe Quellaktivitat aufzeichnet, wahrend das EEG wegen der Volumenleiteigenschaften des Kopfes die gesamte elektrische Aktivitat des Gehirns aufnimmt (Cuffin and Cohen 1979; Lopes da Silva et al. 1991). Welche Auswirkung diese und andere methodische Unterschiede zwischen dem MEG und dem EEG auf die Analyse naturlicher Signale haben, wurde bisher kaum untersucht. Ein einfaches Paradigma dies zu tun, ist die elektrische Registrierung somatosensibel evozierter Potentiale (SEP) synchron mit der Aufzeichnung der magnetischen Felder (SEF).

Somatotopie der fingerstimulierten SEP — Dipolquellen: Lokalisation und 3D-NMR

Die somatotopische Gliederung entlang des Sulcus zentralis ist seit langem bekannt. Mit nicht-invasiven Methoden, dem Mapping von an der Kopfoberflache registrierten SEP (Deiber et al. 1986) und der Dipol-Lokalisation somatosensorischer magnetischer Felder (Baumgartner et al. 1991) konnte die somatotopische Gliederung der Finger entlang des Sulcus zentralis nachvollzogen werden. Untersuchungen der funktionellen Lokalisation relativ zur individuellen Anatomie wurden bisher nur mit invasiven Techniken ausgefuhrt.