Estimating the discretization dependent accuracy of perfusion in coupled capillary flow measurements.

One-compartment models are widely used to quantify hemodynamic parameters such as perfusion, blood volume and mean transit time. These parameters are routinely used for clinical diagnosis and monitoring of disease development and are thus of high relevance. However, it is known that common estimation techniques are discretization dependent and values can be erroneous. In this paper we present a new model that enables systematic quantification of discretization errors. Specifically, we introduce a continuous flow model for tracer propagation within the capillary tissue, used to evaluate state-of-the-art one-compartment models. We demonstrate that one-compartment models are capable of recovering perfusion accurately when applied to only one compartment, i.e. the whole region of interest. However, substantial overestimation of perfusion occurs when applied to fractions of a compartment. We further provide values of the estimated overestimation for various discretization levels, and also show that overestimation can be observed in real-life applications. Common practice of using compartment models for fractions of tissue violates model assumptions and careful interpretation is needed when using the computed values for diagnosis and treatment planning.

Estimation of Large Motion in Lung CT by Integrating Regularized Keypoint Correspondences into Dense Deformable Registration.

We present a novel algorithm for the registration of pulmonary CT scans. Our method is designed for large respiratory motion by integrating sparse keypoint correspondences into a dense continuous optimization framework. The detection of keypoint correspondences enables robustness against large deformations by jointly optimizing over a large number of potential discrete displacements, whereas the dense continuous registration achieves subvoxel alignment with smooth transformations. Both steps are driven by the same normalized gradient fields data term. We employ curvature regularization and a volume change control mechanism to prevent foldings of the deformation grid and restrict the determinant of the Jacobian to physiologically meaningful values. Keypoint correspondences are integrated into the dense registration by a quadratic penalty with adaptively determined weight. Using a parallel matrix-free derivative calculation scheme, a runtime of about 5 min was realized on a standard PC. The proposed algorithm ranks first in the EMPIRE10 challenge on pulmonary image registration. Moreover, it achieves an average landmark distance of 0.82 mm on the DIR-Lab COPD database, thereby improving upon the state of the art in accuracy by 15%. Our algorithm is the first to reach the inter-observer variability in landmark annotation on this dataset.

Segmentation-driven image registration- application to 4D DCE-MRI recordings of the moving kidneys.

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) of the kidneys requires proper motion correction and segmentation to enable an estimation of glomerular filtration rate through pharmacokinetic modeling. Traditionally, co-registration, segmentation, and pharmacokinetic modeling have been applied sequentially as separate processing steps. In this paper, a combined 4D model for simultaneous registration and segmentation of the whole kidney is presented. To demonstrate the model in numerical experiments, we used normalized gradients as data term in the registration and a Mahalanobis distance from the time courses of the segmented regions to a training set for supervised segmentation. By applying this framework to an input consisting of 4D image time series, we conduct simultaneous motion correction and two-region segmentation into kidney and background. The potential of the new approach is demonstrated on real DCE-MRI data from ten healthy volunteers.

3D ultrasound-CT registration of the liver using combined landmark-intensity information.

PURPOSE: An important issue in computer-assisted surgery of the liver is a fast and reliable transfer of preoperative resection plans to the intraoperative situation. One problem is to match the planning data, derived from preoperative CT or MR images, with 3D ultrasound images of the liver, acquired during surgery. As the liver deforms significantly in the intraoperative situation non-rigid registration is necessary. This is a particularly challenging task because pre- and intraoperative image data stem from different modalities and ultrasound images are generally very noisy. METHODS: One way to overcome these problems is to incorporate prior knowledge into the registration process. We propose a method of combining anatomical landmark information with a fast non-parametric intensity registration approach. Mathematically, this leads to a constrained optimization problem. As distance measure we use the normalized gradient field which allows for multimodal image registration. RESULTS: A qualitative and quantitative validation on clinical liver data sets of three different patients has been performed. We used the distance of dense corresponding points on vessel center lines for quantitative validation. The combined landmark and intensity approach improves the mean and percentage of point distances above 3 mm compared to rigid and thin-plate spline registration based only on landmarks. CONCLUSION: The proposed algorithm offers the possibility to incorporate additional a priori knowledge-in terms of few landmarks-provided by a human expert into a non-rigid registration process.

Intensity gradient based registration and fusion of multi-modal images.

OBJECTIVES: A particular problem in image registration arises for multi-modal images taken from different imaging devices and/or modalities. Starting in 1995, mutual information has shown to be a very successful distance measure for multi-modal image registration. Therefore, mutual information is considered to be the state-of-the-art approach to multi-modal image registration. However, mutual information has also a number of well-known drawbacks. Its main disadvantage is that it is known to be highly non-convex and has typically many local maxima. METHODS: This observation motivates us to seek a different image similarity measure which is better suited for optimization but as well capable to handle multi-modal images. RESULTS: In this work, we investigate an alternative distance measure which is based on normalized gradients. CONCLUSIONS: As we show, the alternative approach is deterministic, much simpler, easier to interpret, fast and straightforward to implement, faster to compute, and also much more suitable to numerical optimization.

Intensity gradient based registration and fusion of multi-modal images.

A particular problem in image registration arises for multimodal images taken from different imaging devices and/or modalities. Starting in 1995, mutual information has shown to be a very successful distance measure for multi-modal image registration. However, mutual information has also a number of well-known drawbacks. Its main disadvantage is that it is known to be highly non-convex and has typically many local maxima. This observation motivate us to seek a different image similarity measure which is better suited for optimization but as well capable to handle multi-modal images. In this work we investigate an alternative distance measure which is based on normalized gradients and compare its performance to Mutual Information. We call the new distance measure Normalized Gradient Fields (NGF).

Detecting changes in serial myocardial perfusion SPECT: a simulation study.

BACKGROUND: New algorithms were evaluated for their efficacy in detecting and quantifying serial changes in myocardial perfusion from single photon emission computed tomography (SPECT). METHODS AND RESULTS: We generated 72 simulations with various left ventricular positions, sizes, count rates, and perfusion defect severities using the nonuniform rational B-splines (NURBs)-based CArdiac Torso (NCAT) phantom. Images were automatically aligned by use of both full linear and rigid transformations and quantified for perfusion by use of the CEqual program. Changes within a given perfusion defect were compared by use of a Student t test before and after registration. Registration approaches were compared by use of receiver operating characteristic analysis. Changes of 5% were not detected well in single patients with or without alignment. Changes of 10% and 15% could be detected with false-positive rates of 15% and 10%, respectively, in single studies if alignment was performed before perfusion analysis. Alignment also reduced the number of studies necessary to demonstrate a significant perfusion change (P < .05) in groups of patients by about half. CONCLUSION: Comparison of mean uptake by t values in SPECT perfusion defects can be used to detect 10% and greater differences in serial perfusion studies of single patients. Image alignment is necessary to optimize automatic detection of perfusion changes in both single patients and groups of patients.

Videomicroscopy, image processing, and analysis of whole histologic sections of the human brain.

Serial histologic sections of a whole human brain may have extensions of up to 130 x 130 mm within the coronal plane around the temporal lobe. To date, however, technology has not provided a bright field microscope that is able to shift the object holder continuously in the x- and y-direction over such distances and still possess the same optical capabilities as comparable devices. We developed a new light microscope to continuously quantify such sections. We also developed the computing environment for controlling the device and for analyzing the data produced. In principle, we are now able to quantify each neuron of a human brain. The data ultimately will provide the most detailed structural information about the human brain ascertained thus far. Such detailed information of the spatial distribution of neurons is essential to develop realistic models for simulation of large-scale neuronal networks and to investigate the significance of neuronal arrangements with respect to neuronal signal processing in the CNS. After preprocessing of the data produced by the new microscope, we are able to detect lamination patterns in the spatial distribution of gravity centers of cells. Furthermore, morphological features like size of the projection area and mean staining intensity are visualized as a particle process. The particle process presents the sizes and staining intensity of perikaryons and allows a distinction of gray matter and white matter. These results provide evidence that the system works correctly and can be applied to a systematic analysis of a larger sequence of serial histologic sections. The objective of this study is to introduce the very large section analyzing microscope (VLSAM) and to present the initial data produced by the system. Moreover, we will discuss workload and future developments of the parallel image analysis system that are associated with the microscope.

Visual field representations and locations of visual areas V1/2/3 in human visual cortex.

The position, surface area and visual field representation of human visual areas V1, V2 and V3 were measured using fMRI in 7 subjects (14 hemispheres). Cortical visual field maps of the central 12 deg were measured using rotating wedge and expanding ring stimuli. The boundaries between areas were identified using an automated procedure to fit an atlas of the expected visual field map to the data. All position and surface area measurements were made along the boundary between white matter and gray matter. The representation of the central 2 deg of visual field in areas V1, V2, V3 and hV4 spans about 2100 mm2 and is centered on the lateral-ventral aspect of the occipital lobes at Talairach coordinates -29, -78, -11 and 25, -80, -9. The mean area between the 2-deg and 12-deg eccentricities for the primary visual areas was: V1: 1470 mm2; V2: 1115 mm2; and V3: 819 mm2. The sizes of areas V1, V2 and V3 varied by about a factor of 2.5 across individuals; the sizes of V1 and V2 are significantly correlated within individuals, but there is a very low correlation between V1 and V3. These in vivo measurements of normal human retinotopic visual areas can be used as a reference for comparison to unusual cases involving developmental plasticity, recovery from injury, identifying homology with animal models, or analyzing the computational resources available within the visual pathways.