Julien Jomier

Registration and Analysis of Vascular Images

We have developed a method for rigidly aligning images of tubes. This paper presents an evaluation of the consistency of that method for three-dimensional images of human vasculature. Vascular images may contain alignment ambiguities, poorly corresponding vascular networks, and non-rigid deformations, yet the Monte Carlo experiments presented in this paper show that our method registers vascular images with sub-voxel consistency in a matter of seconds. Furthermore, we show that the methods insensitivity to non-rigid deformations enables the localization, quantification, and visualization of those deformations.Our method aligns a source image with a target image by registering a model of the tubes in the source image directly with the target image. Time can be spent to extract an accurate model of the tubes in the source image. Multiple target images can then be registered with that model without additional extractions.Our registration method builds upon the principles of our tubular object segmentation work that combines dynamic-scale central ridge traversal with radius estimation. In particular, our registration methods consistency stems from incorporating multi-scale ridge and radius measures into the model-image match metric. Additionally, the methods speed is due in part to the use of coarse-to-fine optimization strategies that are enabled by measures made during model extraction and by the parameters inherent to the model-image match metric.

Computer-automated quantification of plus disease in retinopathy of prematurity

BACKGROUNDnIn some cases of retinopathy of prematurity (ROP), it difficult to determine with certainty whether plus disease is present or absent. We have developed a computer program that captures digital images from a video-indirect ophthalmoscope, identifies and traces the major posterior pole blood vessels, measures the dilation and tortuosity of each vessel, and calculates whether or not an eye has plus disease. Our purpose was to determine the accuracy of the computer program in comparison with two masked examiners.nnnMETHODSnA representative sample of posterior pole images from 20 premature infants, 10 normal and 10 representing various degrees of dilation and tortuosity, was extracted from our video database and analyzed by the computer program as well as by two masked examiners experienced in the diagnosis of ROP. The standard photograph from the Cryotherapy for ROP study, representing the minimum degree of dilation and tortuosity required for plus disease, was also digitized, analyzed, and used as a numeric comparison for the automated determination of plus disease.nnnRESULTSnOf the five images determined to have plus disease by both examiners, four were calculated to have plus disease by the computer program (80% sensitivity). Of the 11 images without plus disease, 10 were calculated not to have plus disease by the computer program (91% specificity).nnnCONCLUSIONSnOur computer program has very good sensitivity and specificity compared with masked examiners determination of the presence or absence of plus disease. Automated analysis of dilation and tortuosity of posterior pole blood vessels has the potential to remove subjectivity from the determination of plus disease.

Intra-operative 3D ultrasound augmentation

We introduce an automated and accurate system for registering pre-operative 3D MR and CT images with intraoperative 3D ultrasound images based on the vessels visible in both. The clinical goal is to guide the radio-frequency ablation (RFA) of liver lesions using percutaneous ultrasound even when the lesions are not directly visible using ultrasound. The lesions locations and desired RFA sites are indicated on pre-operative images, and those markings are made to appear within the intra-operative 3D ultrasound images. We present our current implementation, provide analyses of its components, and demonstrate its performance.

Rigid and Deformable Vasculature-to-Image Registration : a Hierarchical Approach

Several recent studies demonstrate the potential of using tubular structures such as vessels as a basis for image registration. In this paper, we present a novel technique for the deformable registration of tubular structures. Our approach aligns tubular models, e.g. vessels of an organ, with an image by combining both rigid and non-rigid transformations in a hierarchical manner. The physical structure and properties of the vessels are taken into account to drive the registration process. Our model-to-image registration method shows sub-voxel accuracy as well as robustness to noise and a convergence time of less than one minute.

Embedding VTK and ITK into a visual programming and rapid prototyping platform

Visualization and image processing of medical datasets has become an essential task for clinical diagnosis support as well as for treatment planning. In order to enable a physician to use and evaluate algorithms within a clinical setting, easily applicable software prototypes with a dedicated user interface are essential. However, substantial programming knowledge is still required today when using powerful open source libraries such as the Visualization Toolkit (VTK) or the Insight Toolkit (ITK). Moreover, these toolkits provide only limited graphical user interface functionality. In this paper, we present the visual programming and rapid prototyping platform MeVisLab which provides flexible and simple handling of visualization and image processing algorithms of VTK/ITK, Open Inventor and the MeVis Image Library by modular visual programming. No programming knowledge is required to set up image processing and visualization pipelines. Complete applications including user interfaces can be easily built within a general framework. In addition to the VTK/ITK features, MeVisLab provides a full integration of the Open Inventor library and offers a state-of-the-art integrated volume renderer. The integration of VTK/ITK algorithms is performed automatically: an XML structure is created from the toolkits source code followed by an automatic module generation from this XML description. Thus, MeVisLab offers a one stop solution integrating VTK/ITK as modules and is suited for rapid prototyping as well as for teaching medical visualization and image analysis. The VTK/ITK integration is available as package of the free version of MeVisLab.

Vascular Atlas Formation Using a Vessel-to-Image Affine Registration Method

We have developed a method for forming vascular atlases using vascular distance maps and a novel vascular model-to-image reg- istration method. Our atlas formation process begins with MR or CT angiogram data from a set of subjects. We extract blood vessels from those data using our tubular object segmentation method. One subjects vascular network model is then chosen as a template, and its vascular distance map (DM) image is computed. Each of the remaining vascular network models is then registered with the DM template using our vascu- lar model-to-image affine registration method. The DM images from the registered vascular models are then computed. The mean and variance images formed from those registered DM images are the vascular atlas. In this paper we apply the atlas formation process to build atlases of normal brain and liver vasculature. We use Monte Carlo simulations to demonstrate the reliability of the underlying registration method. Ad- ditionally, we explain the clinical potential of those atlases and conduct z -score analyses to compare individuals with the atlases to detect abnor- mal vessels.

Automatic vascular tree formation using the mahalanobis distance

We present a novel technique for the automatic formation of vascular trees from segmented tubular structures. Our method combines a minimum spanning tree algorithm with a minimization criterion of the Mahalanobis distance. First, a multivariate class of connected junctions is defined using a set of trained vascular trees and their corresponding image volumes. Second, a minimum spanning tree algorithm forms the tree using the Mahalanobis distance of each connection from the connected class as a cost function. Our technique allows for the best combination of the discrimination criteria between connected and non-connected junctions and is also modality, organ and segmentation specific.

Comparison of vessel segmentations using STAPLE

We propose a novel method for the validation of vascular segmentations. Our technique combines morphological operators and the TAPLE algorithm to obtain ground truth of centerline extractions as well as a measure of accuracy of the methods to be compared. Moreover, ur method can be extended to the validation of any open-curves. We also present a comparison study of three vascular segmentation methods: ridge traversal, statistical and curves level set. They are compared with manual segmentations from five experts.

Automatic quantification of pupil dilation under stress

Response of the autonomic nervous system can be assessed by quantifying the dilation of the pupil of a human placed in darkness. When the intensity of the surrounding light is low, humans pupil dilates to capture a maximum number of photons. This type of dilation is known as dark adaptation. The aim of this study is to test the hypothesis that dark adaptation is slowed proportional to the amount of stress that an individual has experienced. We have developed a new tool for automatic quantification of pupil dilation. Our system uses statistics of the color of the pupil and the iris as well as model-to-image registration and region growing segmentation techniques. Our system has been tested on several images and shows high correlation with hand segmentation.

Combining a Visual Programming and Rapid Prototyping Platform with ITK

In the last few years, the Insight Segmentation and Registration Toolkit (ITK) has become one of the most frequently used open-source libraries for filtering, segmentation, and registration of medical image data. However, a major drawback is its lack of visualization and interaction functionality inside a dedicated development platform. We propose an automatic integration of ITK filters into the visual programming and rapid prototyping platform MeVisLab. Based on an XML description of a filter, an automatic code generation is utilized. Different image types and data dimensions are combined in a single MeVisLab module that can be dynamically handled at runtime. An example application using registration, segmentation, and visualization modules is created in order to show the capabilities of our integration concept.