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Gary E Christensen

Publications and source records attributed to Gary E Christensen.

8 recordsLinked to original sources

Synthesizing average 3D anatomical shapes.

Average shape estimates are often used to characterize normal morphological variation and discriminate dysmorphology in populations. The purpose of this paper is to estimate "average" or the most representative shapes in populations by using high-resolution medical images as input. The "average" shape is computed from high-dimensional spatial transformations used to co-register each subject in the population rather than the image intensities. Inverse consistent image registration is used to help minimize correspondence errors and produce better population average estimates. Testing the method was done using a population of adult MR brain scans from 22 individuals with no know structural abnormalities. Population averages were computed using the spatial transformation method and local changes in morphology were mapped. Results suggest that this method is a feasible means for robust estimation of population average shape. It is also shown that using inverse consistent transformations produces average shape estimates with less error compared to those produced with transformations with nontrivial inverse consistent errors.

Adult↗

Quantitation of the reconstruction quality of a four-dimensional computed tomography process for lung cancer patients.

We have developed a four-dimensional computed tomography (4D CT) technique for mapping breathing motion in radiotherapy treatment planning. A multislice CT scanner (1.5 mm slices) operated in ciné mode was used to acquire 12 contiguous slices in each couch position for 15 consecutive scans (0.5 s rotation, 0.25 s between scans) while the patient underwent simultaneous quantitative spirometry measurements to provide a sorting metric. The spirometry-sorted scans were used to reconstruct a 4D data set. A critical factor for 4D CT is quantifying the reconstructed data set quality which we measure by correlating the metric used relative to internal-object motion. For this study, the internal air content within the lung was used as a surrogate for internal motion measurements. Thresholding and image morphological operations were applied to delineate the air-containing tissues (lungs, trachea) from each CT slice. The Hounsfield values were converted to the internal air content (V). The relationship between the air content and spirometer-measured tidal volume (v) was found to be quite linear throughout the lungs and was used to estimate the overall accuracy and precision of tidal volume-sorted 4D CT. Inspection of the CT-scan air content as a function of tidal volume showed excellent correlations (typically r>0.99) throughout the lung volume. Because of the discovered linear relationship, the ratio of internal air content to tidal volume was indicative of the fraction of air change in each couch position. Theoretically, due to air density differences within the lung and in room, the sum of these ratios would equal 1.11. For 12 patients, the mean value was 1.08 +/- 0.06, indicating the high quality of spirometry-based image sorting. The residual of a first-order fit between v and V was used to estimate the process precision. For all patients, the precision was better than 8%, with a mean value of 5.1% +/- 1.9%. This quantitative analysis highlights the value of using spirometry as the metric in sorting CT scans. The 4D reconstruction provides the CT data required to measure the three-dimensional trajectory of tumor and lung tissue during free breathing.

Air↗

Computed tomography studies of lung mechanics.

The study of lung mechanics has progressed from global descriptions of lung pressure and volume relationships to the high-resolution, three-dimensional, quantitative measurement of dynamic regional mechanical properties and displacements. X-ray computed tomography (CT) imaging is ideally suited to the study of regional lung mechanics in intact subjects because of its high spatial and temporal resolution, correlation of functional data with anatomic detail, increasing volumetric data acquisition, and the unique relationship between CT density and lung air content. This review presents an overview of CT measurement principles and limitations for the study of regional mechanics, reviews some of the early work that set the stage for modern imaging approaches and impacted the understanding and management of patients with acute lung injury, and presents evolving novel approaches for the analysis and application of dynamic volumetric lung image data.

Humans↗

Large deformation inverse consistent elastic image registration.

This paper presents a new image registration algorithm that accommodates locally large nonlinear deformations. The algorithm concurrently estimates the forward and reverse transformations between a pair of images while minimizing the inverse consistency error between the transformations. It assumes that the two images to be registered contain topologically similar objects and were collected using the same imaging modality. The large deformation transformation from one image to the other is accommodated by concatenating a sequence of small deformation transformations. Each incremental transformation is regularized using a linear elastic continuum mechanical model. Results of ten 2D and twelve 3D MR image registration experiments are presented that tested the algorithm's performance on real brain shapes. For these experiments, the inverse consistency error was reduced on average by 50 times in 2D and 30 times in 3D compared to the viscous fluid registration algorithm.

Algorithms↗

Subcortical, cerebellar, and magnetic resonance based consistent brain image registration.

A new landmark-initialized segmentation and intensity-based (LI-SI) inverse-consistent linear elastic image registration algorithm is presented. This method uses manually identified landmarks, segmented volumetric (anatomical) structures, and normalized image signal intensity information to coregister datasets. The features used for image registration and evaluation include 35 cortical, cerebellar, and commissure landmarks manually identified by experts, subcortical and cerebellar regions defined semi-automatically by an artificial neural network and manually trimmed for validity by experts, and tissue classified images that were generated using a discriminant analysis of three magnetic resonance image sets representing T1, T2, and PD modalities. Four groups of results were computed for coregistering 16 datasets with the following registration techniques: rigid registration, extended Talairach registration, intensity-only inverse-consistent linear elastic registration, and the new LI-SI registration. Results are presented showing that relative overlap measurements increased as the dimensionality of the registration algorithm and amount of anatomical information increased. The average relative overlap improved from 0.53 for the rigid registration to 0.55 for the Talairach registration to 0.74 for the intensity-only and to 0.85 for the LI-SI algorithm. We showed a statistically significant improvement for all but one structure using the intensity-only algorithm compared to the Talairach registration. Furthermore, statistically significant improvements for all structures were achieved using the LI-SI algorithm compared to the intensity-only algorithm.

Adult↗

Automatic measurement of the labyrinth using image registration and a deformable inner ear atlas.

RATIONALE AND OBJECTIVES: This article presents a new method for measuring the shape of the cochlea, vestibule, semi-circular canals, and internal auditory canal using image registration and a deformable inner ear atlas. MATERIALS AND METHODS: Computed tomography images of the inner ear are analyzed by placing them into a common orientation and then registering a digital atlas of the inner ear to the data set. The atlas is deformed from its original shape to match the shape of the inner ear in the computed tomography data set using inverse consistent elastic image registration. This process produces an individualized inner ear atlas containing subject-specific measurements and segmentations of the inner ear anatomy in the target computed tomography data set. The shape measurements include the volume and length of the cochlea, vestibule, semi-circular canals, and internal auditory canal; and the angles between the semi-circular canals. RESULTS: A simulated population of inner ear shapes were generated based on the shape of a real population of inner ear shapes and were used to characterize the measurement error of this method. The deformable atlas was used to measure the shape of the left and right inner ear of six individuals. CONCLUSION: Measurement error for 15 of the 24 measurements of our simulated population had an average error of less than 1% and only one measurement had an average error greater than 2.54%. The deformable human inner ear atlas shows promise as a new method for automatically measuring the shape of the labyrinth.

Adult↗

Establishing a normative atlas of the human lung: intersubject warping and registration of volumetric CT images.

RATIONALE AND OBJECTIVES: To establish the range of normal values for quantitative CT-based measures of lung structure and function, the authors developed a method for matching pulmonary structures across individuals and creating a normative human lung atlas. MATERIALS AND METHODS: A computerized human lung atlas was synthesized from computed tomographic (CT) images from six subjects by means of three-dimensional image registration. The authors identified a set of reproducible feature points for each CT image and used these points to establish correspondences across subjects, used a landmark- and intensity-based consistent image registration algorithm to register a template image volume from the population to the rest of the pulmonary CT volumes in the population, averaged these transformations, and constructed an atlas by deforming the template with the average transformation. RESULTS: The effectiveness of the authors' method was evaluated and visualized by means of both gray-level and segmented CT images. The method reduced the average landmark registration error from 10.5 mm to 0.4 mm and the average relative volume overlap error from 0.7 to 0.11 for the six data sets studied. CONCLUSION: The method, and the computerized human lung atlas constructed and visualized by the authors with this method, provides a basis for establishing regional ranges of normative values for structural and functional measures of the human lung.

Algorithms↗