Guido Gerig

Temporal lobe sulco-gyral pattern anomalies in schizophrenia: an in vivo MR three-dimensional surface rendering study

Neuroanatomical and histological findings from post-mortem brains, as well as in vivo findings from magnetic resonance imaging (MRI) studies, suggest the presence of morphologic temporal lobe abnormalities in schizophrenia. To determine whether or not sulco-gyral pattern abnormalities in the temporal lobe could be detected in vivo, we applied computerized surface rendering techniques to MR data sets in order to make both qualitative and quantitative analyses of three-dimensional reconstructions of the temporal and frontal cortex in 15 schizophrenic patients and 15 normal controls. The qualitative analysis, based on a visual classification of the temporal lobe sulco-gyral pattern by 4 raters blind to diagnosis, showed that in schizophrenics there was a more vertical orientation to the sulci in the left temporal lobe, with an interrupted course of sulci due to gyri coursing across the sulci. Normal controls, in contrast, showed a more horizontal orientation with no interruptions. These findings were supported by the quantitative analysis, where more sulcal lines, representing an interrupted course of sulci, were observed in the temporal lobes (more pronounced on the left) in schizophrenics than in normal controls. These data suggest that some of the abnormalities observed in schizophrenia may have their origin in alterations occurring during the course of neurodevelopment when the sulco-gyral pattern is determined.

Compensation of Spatial Inhomogeneity in MRI Based on a Parametric Bias Estimate

A novel bias correction technique is proposed based on the estimation of the parameters of a polynomial bias field directly from image data. The procedure overcomes difficulties known from homomorphic filtering or from techniques assuming an initial presegmented image. The only parameters are a set of expected class means and the standard deviation. Applications to various MR images illustrate the performance.

Image Processing of Routine Spin-Echo MR Images to Enhance Vascular Structures: Comparison with MR Angiography

Magnetic Resonance Imaging (MRI) is a highly flexible diagnostic imaging technique providing complex information about the morphology of various normal and abnormal tissues. Besides this clinically valuable anatomic and pathologic information, there are some unique functional features which can be extracted from MR images. The influence of macroscopic and microscopic motion on MR images as revealed by more or less specialized pulse sequences may demonstrate the presence of physiologically important processes such as blood or cerebrospinal fluid (CSF) flow, tissue perfusion and diffusion [Axel84, Demoulin87, Demoulin89, Haacke89, Wehrli87]. Recent progress in the implementation of these MRI methods shows that while these applications have not yet been fully exploited, their use in clinical practice is not far in the future.

3D Morphometric and Morphologic Information Derived From Clinical Brain MR Images

Data from conventional clinical MR brain images were processed using multi-step computerized segmentation as well as 3D analysis and rendering techniques. The usefulness of so obtained morphometric information and morphologic display for the development of new concepts for diagnosis and follow up of diseases was demonstrated with data sets from patients with Alzheimer’s disease, normal pressure hydrocephalus, multiple sclerosis and brain tumors.

Segmentation and Analysis of Multidimensional Data-Sets in Medicine

Segmentation and analysis of 2-D and 3-D CT and MR data sets is illustrated on examples covering renal function studies in MR time sequences, discrimination of brain matter in multispectral 3-D MRI, extraction of brain tumor by structure segmentation methods, and model guided analysis of hip-joint and pelvic anatomy. It is argued in favor of a tightly integrated analysis sequence which exploits the characteristics of the original measurements and all available anatomic information. Knowledge-based analysis has produced some preliminary results but must be considered still in its infancy. Novel ideas for describing and representing natural structures in conjunction with AI tools are needed for generally applicable analysis methods.

Combining Two Imaging Modalities for Neuroradiological Diagnosis: 3D Representation of Cerebral Blood Vessels

Today the integration of information from different imaging modalities in medicine such as Computer Tomography or Magnetic Resonance Imaging (MRI) is left to the physician and gets little support from computers. In the case of neuroradiological diagnosis, information about cerebral blood vessels is available from 3D volume data from Magnetic Resonance Angiography (MRA) and from 2D images generated by Digital Subtraction Angiography (DSA). The DSA images have a higher resolution than MRA data, and therefore neuroradiologists are highly interested in a 3D reconstruction of cerebral blood vessels from different DSA projections. On the other hand, MRA contains important functional information, the velocity of blood flow. This paper describes work in progress to make available to the physician the full 3D information from both imaging modalities including an approach to 3D reconstruction from DSA im ages which makes use of the MRA data. The 3D DSA reconstruction also opens the way to an integration of information from DSA with completely different types of information, for example information on anatomical structure or soft tissue from MRI. An integral part of this work is a pilot system for clinical validation.

Automatic Segmentation of Cell Nuclei from Confocal Laser Scanning Microscopy Images

In this paper we present a method for the fully automatic segmentation of cell nuclei from 3D confocal laser microscopy images. The method is based on the combination of previously proposed techniques which have been refined for the requirements of this task. A 3D extension of a wave propagation technique applied to gradient magnitude images allows us a precise initialization of elastically deformable Fourier models and therefore a fully automatic image analysis. The shape parameters are transformed into invariant descriptors and provide the basis of a statistical analysis of cell nucleus shapes. This analysis will be carried out in order to determine average intersection lengths between cell nuclei and single particle tracks of ionizing radiation. This allows a quantification of absorbed energy on living cells leading to a better understanding of the biological significance of exposure to radiation in low doses.

Detecting and Inferring Brain Activation from Functional MRI by Hypothesis-Testing Based on the Likelihood Ratio

For the measure of brain activation in functional MRI many methods compute a heuristically chosen metric. The statistic of the underlying metric which is implicitly derived from the original assumption about the noise in the data, provides only an indirect way to the statistical inference of brain activation. An alternative procedure is proposed by presenting a binary hypothesis-testing approach. This approach treats the problem of detecting brain activation by directly deriving a test statistic based on the probabilistic model of the noise in the data. Thereby, deterministic and parameterized models for the hemodynamic response can be considered. Results show that time series models can be detected even if they are characterized by unknown parameters, associated with the unclear nature of the mechanisms that mediate between neuronal stimulation and hemodynamic brain response. The likelihood ratio tests proposed in this paper are very efficient and robust in making a statistical inference about detected regions of brain activation. To validate the applicability of the approach a simulation environment for functional MRI is used. This environment also serves as a testbed for comparative study and systematic tests.

3D Verdünnung zur symbolischen Beschreibung von verästelten, räumlichen Strukturen

Die Analyse von 3-D Strukturen erfordert Segmentierung und objektzentrierte Beschreibung. Wahrend bei der Segmentierung von 3-D Bilddaten Erfolge erzielt wurden, stehen Beschreibungsmethoden, die Zugriff auf geometrische Formkriterien erlauben, immer noch weitgehend aus.

A Hardware And Software Optimized Program System For Interactive Image Processing

An interactive image processing system was set up to provide easy use of standard methods and their rapid execution. Point operations and linear and non-linear neighborhood operations were implemented on the display system for integer valued images and on the host for their floating point representation. Fourier domain processing was accelerated by using the refresh memories for auxiliary direct access storage and by computing the PFT with assembly coded routines. Topological operations for segmentation of binary images are done in the display system. Image classification with instant display of the results equally relies on the display hardware. A command processor parses input to verify and validate commands and to separate them from (optional) parameters specified by the user if given default values are not suitable. Usage and integration of image processing procedures is facilitated by maintaining all command language features of the host operating system. Command strings can be set up to repeat sequences of processing steps. A help facility serves to inform the less experienced user.