Hrvoje Bogunovic

Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms.

Efficiently obtaining a reliable coronary artery centerline from computed tomography angiography data is relevant in clinical practice. Whereas numerous methods have been presented for this purpose, up to now no standardized evaluation methodology has been published to reliably evaluate and compare the performance of the existing or newly developed coronary artery centerline extraction algorithms. This paper describes a standardized evaluation methodology and reference database for the quantitative evaluation of coronary artery centerline extraction algorithms. The contribution of this work is fourfold: (1) a method is described to create a consensus centerline with multiple observers, (2) well-defined measures are presented for the evaluation of coronary artery centerline extraction algorithms, (3) a database containing 32 cardiac CTA datasets with corresponding reference standard is described and made available, and (4) 13 coronary artery centerline extraction algorithms, implemented by different research groups, are quantitatively evaluated and compared. The presented evaluation framework is made available to the medical imaging community for benchmarking existing or newly developed coronary centerline extraction algorithms.

Automated segmentation of cerebral vasculature with aneurysms in 3DRA and TOF-MRA using geodesic active regions: an evaluation study.

PURPOSE To evaluate the suitability of an improved version of an automatic segmentation method based on geodesic active regions (GAR) for segmenting cerebral vasculature with aneurysms from 3D x-ray reconstruction angiography (3DRA) and time of flight magnetic resonance angiography (TOF-MRA) images available in the clinical routine. METHODS Three aspects of the GAR method have been improved: execution time, robustness to variability in imaging protocols, and robustness to variability in image spatial resolutions. The improved GAR was retrospectively evaluated on images from patients containing intracranial aneurysms in the area of the Circle of Willis and imaged with two modalities: 3DRA and TOF-MRA. Images were obtained from two clinical centers, each using different imaging equipment. Evaluation included qualitative and quantitative analyses of the segmentation results on 20 images from 10 patients. The gold standard was built from 660 cross-sections (33 per image) of vessels and aneurysms, manually measured by interventional neuroradiologists. GAR has also been compared to an interactive segmentation method: isointensity surface extraction (ISE). In addition, since patients had been imaged with the two modalities, we performed an intermodality agreement analysis with respect to both the manual measurements and each of the two segmentation methods. RESULTS Both GAR and ISE differed from the gold standard within acceptable limits compared to the imaging resolution. GAR (ISE) had an average accuracy of 0.20 (0.24) mm for 3DRA and 0.27 (0.30) mm for TOF-MRA, and had a repeatability of 0.05 (0.20) mm. Compared to ISE, GAR had a lower qualitative error in the vessel region and a lower quantitative error in the aneurysm region. The repeatability of GAR was superior to manual measurements and ISE. The intermodality agreement was similar between GAR and the manual measurements. CONCLUSIONS The improved GAR method outperformed ISE qualitatively as well as quantitatively and is suitable for segmenting 3DRA and TOF-MRA images from clinical routine.

Patient-specific computational hemodynamics of intracranial aneurysms from 3D rotational angiography and CT angiography: an in vivo reproducibility study

BACKGROUND AND PURPOSE: Patient-specific simulations of the hemodynamics in intracranial aneurysms can be constructed by using image-based vascular models and CFD techniques. This work evaluates the impact of the choice of imaging technique on these simulations. MATERIALS AND METHODS: Ten aneurysms, imaged with 3DRA and CTA, were analyzed to assess the reproducibility of geometric and hemodynamic variables across the 2 modalities. RESULTS: Compared with 3DRA models, we found that CTA models often had larger aneurysm necks (P = .05) and that most of the smallest vessels (between 0.7 and 1.0 mm in diameter) could not be reconstructed successfully with CTA. With respect to the values measured in the 3DRA models, the flow rate differed by 14.1 ± 2.8% (mean ± SE) just proximal to the aneurysm and 33.9 ± 7.6% at the aneurysm neck. The mean WSS on the aneurysm differed by 44.2 ± 6.0%. Even when normalized to the parent vessel WSS, a difference of 31.4 ± 9.9% remained, with the normalized WSS in most cases being larger in the CTA model (P = .04). Despite these substantial differences, excellent agreement (κ ≥ 0.9) was found for qualitative variables that describe the flow field, such as the structure of the flow pattern and the flow complexity. CONCLUSIONS: Although relatively large differences were found for all evaluated quantitative hemodynamic variables, the main flow characteristics were reproduced across imaging modalities.

Three-dimensional automated choroidal volume assessment on standard spectral-domain optical coherence tomography and correlation with the level of diabetic macular edema.

PURPOSE To measure choroidal thickness on spectral-domain optical coherence tomography (SD OCT) images using automated algorithms and to correlate choroidal pathology with retinal changes attributable to diabetic macular edema (DME). DESIGN Post hoc analysis of multicenter clinical trial baseline data. METHODS SD OCT raster scans/fluorescein angiograms were obtained from 284 treatment-naïve eyes of 142 patients with clinically significant DME and from 20 controls. Three-dimensional (3D) SD OCT images were evaluated by a certified independent reading center analyzing retinal changes associated with diabetic retinopathy. Choroidal thicknesses were analyzed using a fully automated algorithm. Angiograms were assessed manually. Multiple endpoint correction according to Bonferroni-Holm was applied. Main outcome measures were average retinal/choroidal thickness on fovea-centered or peak of edema (thickest point of edema)-centered Early Treatment Diabetic Retinopathy Study grid, maximum area of leakage, and the correlation between retinal and choroidal thicknesses. RESULTS Total choroidal thickness is significantly reduced in DME (175 ± 23 μm; P = .0016) and nonedematous fellow eyes (177 ± 20 μm; P = .009) of patients compared with healthy control eyes (190 ± 23 μm). Retinal/choroidal thickness values showed no significant correlation (1-mm: P = .27, r(2) = 0.01; 3-mm: P = .96, r(2) < 0.0001; 6-mm: P = .42, r(2) = 0.006). No significant difference was found in the 1- or 3-mm circle of a retinal peak of edema-centered grid. All other measurements of choroidal/retinal thickness (DME vs healthy, DME vs peak of edema-centered, DME vs fellow, healthy vs fellow, peak of edema-centered vs healthy, peak of edema-centered vs fellow eyes) were compared but no statistically significant correlation was found. By tendency a thinner choroid correlates with larger retinal leakage areas. CONCLUSIONS Automated algorithms can be used to reliably assess choroidal thickness in eyes with DME. Choroidal thickness was generally reduced in patients with diabetes if DME is present in 1 eye; however, no correlation was found between choroidal/retinal pathologies, suggesting different pathogenetic pathways.

Face image validation system

In this paper, we present a novel face image validation system. The purpose of the system is to evaluate quality of face images for identification documents and to detect face images that do not satisfy the image quality requirements. To determine image quality the system first performs face detection in order to find facial features and determine image background. The system consists of seventeen separate tests. Each test checks one quality aspect of the face or of the whole image and compares it to the requirements of International Civil Aviation Organization (ICAO) proposals for machine readable travel documents. The requirements are designed to ensure good conditions for automatic face recognition. The tests are organized in a hierarchical way so the low-level tests are executed first and the high-level tests are executed last. The result of a test is a fuzzy value representing a measure of the image quality. Each test has a set of parameters that can be tuned to produce desired performance of the test. Initial testing of the system has been performed on the set of 190 face images and has demonstrated the feasibility of the method.

Automated landmarking and geometric characterization of the carotid siphon

The geometry of the carotid siphon has a large variability between subjects, which has prompted its study as a potential geometric risk factor for the onset of vascular pathologies on and off the internal carotid artery (ICA). In this work, we present a methodology for an objective and extensive geometric characterization of carotid siphon parameterized by a set of anatomical landmarks. We introduce a complete and automated characterization pipeline. Starting from the segmentation of vasculature from angiographic image and its centerline extraction, we first identify ICA by characterizing vessel tree bifurcations and training a support vector machine classifier to detect ICA terminal bifurcation. On ICA centerline curve, we detect anatomical landmarks of carotid siphon by modeling it as a sequence of four bends and selecting their centers and interfaces between them. Bends are detected from the trajectory of the curvature vector expressed in the parallel transport frame of the curve. Finally, using the detected landmarks, we characterize the geometry in two complementary ways. First, with a set of local and global geometric features, known to affect hemodynamics. Second, using large deformation diffeomorphic metric curve mapping (LDDMCM) to quantify pairwise shape similarity. We processed 96 images acquired with 3D rotational angiography. ICA identification had a cross-validation success rate of 99%. Automated landmarking was validated by computing limits of agreement with the reference taken to be the locations of the manually placed landmarks averaged across multiple observers. For all but one landmark, either the bias was not statistically significant or the variability was within 50% of the inter-observer one. The subsequently computed values of geometric features and LDDMCM were commensurate to the ones obtained with manual landmarking. The characterization based on pair-wise LDDMCM proved better in classifying the carotid siphon shape classes than the one based on geometric features. The proposed characterization provides a rich description of geometry and is ready to be applied in the search for geometric risk factors of the carotid siphon.

Anatomical Labeling of the Circle of Willis Using Maximum A Posteriori Probability Estimation

Anatomical labeling of the cerebral arteries forming the Circle of Willis (CoW) enables inter-subject comparison, which is required for geometric characterization and discovering risk factors associated with cerebrovascular pathologies. We present a method for automated anatomical labeling of the CoW by detecting its main bifurcations. The CoW is modeled as rooted attributed relational graph, with bifurcations as its vertices, whose attributes are characterized as points on a Riemannian manifold. The method is first trained on a set of pre-labeled examples, where it learns the variability of local bifurcation features as well as the variability in the topology. Then, the labeling of the target vasculature is obtained as maximum a posteriori probability (MAP) estimate where the likelihood of labeling individual bifurcations is regularized by the prior structural knowledge of the graph they span. The method was evaluated by cross-validation on 50 subjects, imaged with magnetic resonance angiography, and showed a mean detection accuracy of 95%. In addition, besides providing the MAP, the method can rank the labelings. The proposed method naturally handles anatomical structural variability and is demonstrated to be suitable for labeling arterial segments of the CoW.

Automatic Aneurysm Neck Detection Using Surface Voronoi Diagrams

A new automatic approach for saccular intracranial aneurysm isolation is proposed in this work. Due to the inter- and intra-observer variability in manual delineation of the aneurysm neck, a definition based on a minimum cost path around the aneurysm sac is proposed that copes with this variability and is able to make consistent measurements along different data sets, as well as to automate and speedup the analysis of cerebral aneurysms. The method is based on the computation of a minimal path along a scalar field obtained on the vessel surface, to find the aneurysm neck in a robust and fast manner. The computation of the scalar field on the surface is obtained using a fast marching approach with a speed function based on the exponential of the distance from the centerline bifurcation between the aneurysm dome and the parent vessels. In order to assure a correct topology of the aneurysm sac, the neck computation is constrained to a region defined by a surface Voronoi diagram obtained from the branches of the vessel centerline. We validate this method comparing our results in 26 real cases with manual aneurysm isolation obtained using a cut-plane, and also with results obtained using manual delineations from three different observers by comparing typical morphological measures.

Estimating perfusion using X-ray angiography

In this paper we present a method for extraction of functional information from a time-sequence of X-ray angiographic images. By observing contrast agent propagation profile in a region of the angiogram one can calculate a number of parameters of that profile. Each parameter can be used to construct a parametric image of the imaged area. Such parametric images present a functional rather than morphological aspect of the tissue. The most important functional parameter is perfusion. Perfusion is defined as a blood flow at the capillary level and is commonly used to detect ischemic areas. Perfusion CT and perfusion MRI (pMRI) modalities have commonly been used to extract perfusion data. In this paper, a new method for calculation of perfusion from the contrast agent profile of a sequence of X-ray angiograms is presented. The method utilizes Wiener filtering for denoising of time signals. The experimental results are computed on a sequence of cerebral angiograms.

Relationships of Retinal Structure and Humphrey 24-2 Visual Field Thresholds in Patients With Glaucoma

PURPOSE To determine relationships between spectral-domain optical coherence tomography (SD-OCT) derived regional damage to the retinal ganglion cell-axonal complex (RGC-AC) and visual thresholds for each location of the Humphrey 24-2 visual field, in all stages of open-angle glaucoma. METHODS Patients with early, moderate, and advanced glaucoma were recruited from a tertiary glaucoma clinic. Humphrey 24-2 and 9-field Spectralis SD-OCT were acquired for each subject. Individual OCT volumes were aligned, nerve fiber layer (NFL), ganglion cell and inner plexiform layers (GCL+IPL) cosegmented. These layers were then partitioned into 54 sectors corresponding to the 24-2 grid. A Support Vector Machine was trained independently for each sector to predict the sector threshold, using these structural properties. RESULTS One hundred twenty-two consecutive subjects, 43 early, 39 moderate, and 40 advanced, glaucoma were included (122 eyes). Average correlation coefficient (R) was 0.68 (0.47-0.82), and average root mean square error (RMSE) was 6.92 dB (3.93-8.68 dB). Prediction performance averaged over the entire field, superior hemifield, and inferior hemifield had R (RMSE) values of 0.77 (3.76), 0.80 (5.05), and 0.84 (3.80) dB, respectively. CONCLUSIONS Predicting individual 24-2 visual field thresholds from structural information derived from nine-field SD-OCT local NFL and GCL+IPL thicknesses using the RGC-AC concept is feasible, showing the potential for the predictive ability of SD-OCT structural information for visual function. Ultimately, it may be feasible to complement and reduce the burden of subjective visual field testing in glaucoma patients with predicted function derived objectively from OCT.