Lumen Boundaries Research Articles

Lumen boundary detection using neutrosophic c-means in IVOCT images

In this paper, a novel method for lumen boundary identification is proposed using Neutrosophic c_means. This method clusters pixels of the intravascular optical coherence tomography image into several clusters using indeterminacy and Neutrosophic theory, which aims to detect the boundaries. Intravascular optical coherence tomography images are cross-sectional and high-resolution images which are taken from the coronary arterial wall. Coronary Artery Disease cause a lot of death each year. The first step for diagnosing this kind of diseases is to detect lumen boundary. Employing this approach, we obtained 0.972, 0.019, 0.076 mm2, 0.32 mm, and 0.985 as mean value for Jaccard measure (JACC), the percentage of area difference (PAD), average distance (AD), Hausdorff distance (HD), and dice index (DI), respectively. Based on our results, this method enjoys high accuracy performance.

Endoscopic resection for subepithelial lesions-pure endoscopic full-thickness resection and submucosal tunneling endoscopic resection.

Endoscopic full-thickness resection (EFTR) and submucosal tunneling endoscopic resection (STER) are the frontier of therapeutic endoscopic. These two methods rely on the skillset and equipment of endoscopic submucosal dissection (ESD) while going beyond the boundaries of the gastrointestinal lumen. They are both representatives of natural orifice transluminal endoscopic surgery, with STER being a direct off-shoot of peroral endoscopic myotomy (POEM). Both techniques are designed for the removal of gastrointestinal tumors originating from the muscularis propria but tend to be used in different organs and come with respective challenges. In this review we will go over the history, indication, technique and literature of these two techniques.

Dynamic optical coherence tomography imaging of the lacrimal passage with an extrinsic contrast agent.

Recently, in vivo trans-conjunctiva optical coherence tomography (OCT) imaging of the lacrimal passage was demonstrated using a turbid commercial eye drop as an extrinsic contrast agent. However, static OCT images are not sufficient to unambiguously delineate the lumen boundary to render 3D lumen images of the lacrimal passage by segmentation. The turbid eye drop is expected to include small particles that flow and undergo Brownian motion and can be used as an extrinsic contrast agent for dynamic OCT. We conducted dynamic OCT measurements of the lacrimal passage using a swept source OCT system. Firstly, characterization of the dynamic OCT properties of the eye drop was performed. For improved delineation of the lumen boundary, we calculated the sum of the squared differences of intensities with two different normalization parameters. By making composite color images from OCT images and these two dynamic OCT images, we could execute unambiguous segmentation of the lumen of the lacrimal passage. Three-dimensional volumetric images of parts of the lacrimal passage, i.e., lacrimal canaliculus and lacrimal punctum, are demonstrated.

Lumen boundaries extracted from coronary computed tomography angiography on computed fractional flow reserve (FFRCT): validation with optical coherence tomography.

The aim of this study was to evaluate the accuracy of minimum lumen area (MLA) by coronary computed tomography angiography (cCTA) and its impact on fractional flow reserve (FFRCT). Fifty-seven patients (118 lesions, 72 vessels) who underwent cCTA and optical coherence tomography (OCT) were enrolled. OCT and cCTA were co-registered and MLAs were measured with both modalities. FFROCT was calculated using OCT-updated models with cCTA-based lumen geometry replaced by OCT-derived geometry. Lesions were grouped by Agatston score (AS) and minimum lumen diameter (MLD) using the OCT catheter and guidewire size (1.0 mm) as a threshold. For all lesions, the average absolute difference between cCTA and OCT MLA was 0.621±0.571 mm2. Pearson correlation coefficients between cCTA and OCT MLAs in lesions with low-intermediate and high AS were 0.873 and 0.787, respectively (both p<0.0001). Irrespective of AS score, excellent correlations were observed for MLA (r=0.839, p<0.0001) and FFR comparisons (r=0.918, p<0.0001) in lesions with MLD ≥1.0 mm but not for lesions with MLD <1.0 mm. The spatial resolution of cCTA or calcification does not practically limit the accuracy of lumen boundary identification by cCTA or FFRCT calculations for MLD ≥1.0 mm. The accuracy of cCTA MLA could not be adequately assessed for lesions with MLD <1.0 mm.

Carotid plaque segmentation from three-dimensional ultrasound images by direct three-dimensional sparse field level-set optimization

Total plaque volume (TPV) measured from 3D carotid ultrasound has been shown to be able to predict cardiovascular events and is sensitive in detecting treatment effects. Manual plaque segmentation was performed in previous studies to quantify TPV, but is tedious, requires long training times and is prone to observer variability. This article introduces the first 3D direct volume-based level-set algorithm to segment plaques from 3D carotid ultrasound images. The plaque surfaces were first initialized based on the lumen and outer wall boundaries generated by a previously described semi-automatic algorithm and then deformed by a direct three-dimensional sparse field level-set algorithm, which enforced the longitudinal continuity of the segmented plaque surfaces. This is a marked advantage as compared to a previously proposed 2D slice-by-slice plaque segmentation method. In plaque boundary initialization, the previous technique performed a search on lines connecting corresponding point pairs of the outer wall and lumen boundaries. A limitation of this initialization strategy was that an inaccurate initial plaque boundary would be generated if the plaque was not enclosed entirely by the wall and lumen boundaries. A mechanism is proposed to extend the search range in order to capture the entire plaque if the outer wall boundary lies on a weak edge in the 3D ultrasound image. The proposed method was compared with the previously described 2D slice-by-slice plaque segmentation method in 26 three-dimensional carotid ultrasound images containing 27 plaques with volumes ranging from 12.5 to 450.0 mm3. The manually segmented plaque boundaries serve as the surrogate gold standard. Segmentation accuracy was quantified by volume-, area- and distance-based metrics, including absolute plaque volume difference (|ΔPV|), Dice similarity coefficient (DSC), mean and maximum absolute distance (MAD and MAXD). The proposed direct 3D plaque segmentation algorithm was associated with a significantly lower |ΔPV|, MAD and MAXD, and a significantly higher DSC compared to the previously described slice-by-slice algorithm (|ΔPV|:p=0.012, DSC: p=2.1×10−4, MAD: p=1.3×10−4, MAXD: p=5.2×10−4). The proposed 3D volume-based algorithm required 72±22 s to segment a plaque, which is 40% lower than the 2D slice-by-slice algorithm (114±18 s). The proposed automatic plaque segmentation method generates accurate and reproducible boundaries efficiently and will allow for streamlining plaque quantification based on 3D ultrasound images.

Learning-based automated segmentation of the carotid artery vessel wall in dual-sequence MRI using subdivision surface fitting.

The quantification of vessel wall morphology and plaque burden requires vessel segmentation, which is generally performed by manual delineations. The purpose of our work is to develop and evaluate a new 3D model-based approach for carotid artery wall segmentation from dual-sequence MRI. The proposed method segments the lumen and outer wall surfaces including the bifurcation region by fitting a subdivision surface constructed hierarchical-tree model to the image data. In particular, a hybrid segmentation which combines deformable model fitting with boundary classification was applied to extract the lumen surface. The 3D model ensures the correct shape and topology of the carotid artery, while the boundary classification uses combined image information of 3D TOF-MRA and 3D BB-MRI to promote accurate delineation of the lumen boundaries. The proposed algorithm was validated on 25 subjects (48 arteries) including both healthy volunteers and atherosclerotic patients with 30% to 70% carotid stenosis. For both lumen and outer wall border detection, our result shows good agreement between manually and automatically determined contours, with contour-to-contour distance less than 1 pixel as well as Dice overlap greater than 0.87 at all different carotid artery sections. The presented 3D segmentation technique has demonstrated the capability of providing vessel wall delineation for 3D carotid MRI data with high accuracy and limited user interaction. This brings benefits to large-scale patient studies for assessing the effect of pharmacological treatment of atherosclerosis by reducing image analysis time and bias between human observers.

Semi-automated carotid lumen segmentation in computed tomography angiography images.

Carotid artery stenosis causes narrowing of carotid lumens and may lead to brain infarction. The purpose of this study was to develop a semi-automated method of segmenting vessel walls, surrounding tissues, and more importantly, the carotid artery lumen by contrast computed tomography angiography (CTA) images and to define the severity of stenosis and present a three-dimensional model of the carotid for visual inspection.In vivo contrast CTA images of 14 patients (7 normal subjects and 7 patients undergoing endarterectomy) were analyzed using a multi-step segmentation algorithm. This method uses graph cut followed by watershed and Hessian based shortest path method in order to extract lumen boundary correctly without being corrupted in the presence of surrounding tissues. Quantitative measurements of the proposed method were compared with those of manual delineation by independent board-certified radiologists. The results were quantitatively evaluated using spatial overlap surface distance indices. A slightly strong match was shown in terms of dice similarity coefficient (DSC) = 0.87±0.08; mean surface distance (Dmsd) = 0.32±0.32; root mean squared surface distance (Drmssd) = 0.49±0.54 and maximum surface distance (Dmax) = 2.14±2.08 between manual and automated segmentation of common, internal and external carotid arteries, carotid bifurcation and stenotic artery, respectively. Quantitative measurements showed that the proposed method has high potential to segment the carotid lumen and is robust to the changes of the lumen diameter and the shape of the stenosis area at the bifurcation site. The proposed method for CTA images provides a fast and reliable tool to quantify the severity of carotid artery stenosis.

Automatic segmentation of coronary morphology using transmittance-based lumen intensity-enhanced intravascular optical coherence tomography images and applying a localized level-set-based active contour method.

Lumen segmentation from clinical intravascular optical coherence tomography (IV-OCT) images has clinical relevance as it provides a full three-dimensional perspective of diseased coronary artery sections. Inaccurate segmentation may occur when there are artifacts in the image, resulting from issues such as inadequate blood clearance. This study proposes a transmittance-based lumen intensity enhancement method that ensures only lumen regions are highlighted. A level-set-based active contour method that utilizes the local speckle distribution properties of the image is then employed to drive an image-specific active contour toward the true lumen boundaries. By utilizing local speckle properties, the intensity variation issues within the image are resolved. This combined approach has been successfully applied to challenging clinical IV-OCT datasets that contains multiple lumens, residual blood flow, and its shadowing artifact. A method to identify the guide-wire and interpolate the lost lumen segments has been implemented. This approach is fast and can be performed even when guide-wire boundaries are not easily identified. Lumen enhancement also makes it easy to identify vessel side branches. This automated approach is not only able to extract the arterial lumen, but also the smaller microvascular lumens that are associated with the vasa vasorum and with atherosclerotic plaque.

Ultrasound-Based Automated Carotid Lumen Diameter/Stenosis Measurement and its Validation System

Objective Degree of carotid stenosis is an important predictor to assess risk of stroke. Systolic velocity-based methods for lumen diameter and stenosis measurement are subjective. Image-based methods face a challenge because of low gradients in media and intima walls. Methods This article presents AtheroEdge™ 2.0, a two-stage process for automated carotid lumen diameter measurement that combats the above challenges. Stage one uses spectral analysis based on the hypothesis that far-wall adventitia is brightest. Stage two uses lumen pixel region identification based on the assumption that blood flow has constant density. Using global and local processing, lumen boundaries are detected. This clinical system outputs lumen diameter along with stenosis severity index (SSI). Results Our database consists of institutional review board–approved 202 patients (males/females: 155/47) left and right common carotid artery images (404 images, Toshiba scanner). Two trained neuro radiologists performed manual lumen border tracings using ImgTracer™ software. The coefficient of correlation between automated and two manual readings was 0.91 and 0.92. Dice similarity and Jaccard index were 95.82%, 95.72% and 92.10%, 91.92%, respectively. The mean diameter error between automated and two manual readings was 0.27 ± 0.26 and 0.26 ± 0.28 mm, respectively. Precision of merit was 98.05% and 99.03% with respect to two readings. SSI showed 97% accuracy. Conclusions The image-based automated carotid lumen diameter and stenosis measurement system is fast, accurate, and reliable.

Preliminary results for the supervised detection of lumen and stent from OCT pullbacks

In cardiology, optical coherence tomography (OCT) has been established as a reference for in vivo intravascular image. OCT provides high-resolution and enables us to visualize accurately vessel intimal layers and stents. The drawback is the time necessary to manually select stent struts and lumen boundary. We developed and evaluated an automatic stent strut detection method to apply to intravascular OCT images. The proposed approach innovates the strut shadow detection, which can be considered as an independent processing step that helps discriminating struts by using a profile map. The paper will be presented as a complete process, explaining the necessary steps in order of appearance.

Automatic Coronary Artery Segmentation Using Active Search for Branches and Seemingly Disconnected Vessel Segments from Coronary CT Angiography.

We propose a Bayesian tracking and segmentation method of coronary arteries on coronary computed tomographic angiography (CCTA). The geometry of coronary arteries including lumen boundary is estimated in Maximum A Posteriori (MAP) framework. Three consecutive sphere based filtering is combined with a stochastic process that is based on the similarity of the consecutive local neighborhood voxels and the geometric constraint of a vessel. It is also founded on the prior knowledge that an artery can be seen locally disconnected and consist of branches which may be seemingly disconnected due to plaque build up. For such problem, an active search method is proposed to find branches and seemingly disconnected but actually connected vessel segments. Several new measures have been developed for branch detection, disconnection check and planar vesselness measure. Using public domain Rotterdam CT dataset, the accuracy of extracted centerline is demonstrated and automatic reconstruction of coronary artery mesh is shown.

Asymmetric pulsation of rat carotid artery bifurcation in three-dimension observed by ultrasound imaging.

The arterial structure cyclically fluctuates in three-dimensions (3-D) caused by pulsatile blood flow. The evaluation of arterial wall motion and hemodynamics contributes to early diagnosis of carotid atherosclerosis. Ultrasound is one of the most appropriate imaging modalities to evaluate arterial wall motion in real time. Although many previous studies have discussed the mechanical properties of the carotid artery bifurcation (CAB) from the two-dimensional (2-D) view, the spatio-temporal variation of carotid artery geometry in 3-D has not yet been investigated in detail. In this study, the 3-D data set of CAB from rats was acquired using a high spatio-temporal resolution ultrasound imaging system with a 40MHz probe using mechanical sector scanning. A total of 31 slices of cross-section images were stored and a spoke scan algorithm was implemented to radially scan the lumen area in polar coordinates based on a pre-tracked seed point. The boundary of the arterial lumen was segmented using intensity-threshold-based boundary detection and fitted by polynomial regression. Two operators, who were trained with the same protocol to minimize inter- and intra-operator variability, manually segmented the lumen boundary on systolic and diastolic phase from the gray-scale images. Finally, the 3-D lumen geometries of CAB during one cardiac cycle were constructed based on the segmented lumen boundaries. From this constructed 3-D geometry, we observed that the CAB geometry favorably expanded to the anterior/posterior direction, parallel to the sagittal plane; and the manually segmented geometry also confirmed the asymmetrical change in bifurcation geometry. This is the first study on visualization and quantification on the asymmetrical variation of the CAB geometry of a rat in 3-D during a whole cardiac cycle. This finding may be useful in understanding hemodynamic etiology of various cardiovascular diseases such as arterial stenosis and its complications, and also provides reference information for numerical simulation studies on arterial wall motion.

Automatic detection of aorto-femoral vessel trajectory from whole-body computed tomography angiography data sets.

Extraction of the aorto-femoral vessel trajectory is important to utilize computed tomography angiography (CTA) in an integrated workflow of the image-guided work-up prior to trans-catheter aortic valve replacement (TAVR). The aim of this study was to develop a new, fully-automated technique for the extraction of the entire arterial access route from the femoral artery to the aortic root. An automatic vessel tracking algorithm was first used to find the centerline that connected the femoral accessing points and the aortic root. Subsequently, a deformable 3D-model fitting method was used to delineate the lumen boundary of the vascular trajectory in the whole-body CTA dataset. A validation was carried out by comparing the automatically obtained results with semi-automatically obtained results from two experienced observers. The whole framework was validated on whole body CTA datasets of 36 patients. The average Dice similarity indexes between the segmentations of the automatic method and observer 1 for the left ilio-femoral artery, the right ilio-femoral artery and the aorta were 0.977 ± 0.030, 0.980 ± 0.019, 0.982 ± 0.016; the average Dice similarity indexes between the segmentations of the automatic method and observer 2 were 0.950 ± 0.040, 0.954 ± 0.031 and 0.965 ± 0.019, respectively. The inter-observer variability resulted in a Dice similarity index of 0.954 ± 0.038, 0.952 ± 0.031 and 0.969 ± 0.018 for the left ilio-femoral artery, the right ilio-femoral artery and the aorta. The average minimal luminal diameters (MLDs) of the ilio-femoral artery were 6.03 ± 1.48, 5.70 ± 1.43 and 5.52 ± 1.32mm for the automatic method, observer 1 and observer 2 respectively. The MLDs of the aorta were 13.43 ± 2.54, 12.40 ± 2.93 and 12.08 ± 2.40mm for the automatic method, observer 1 and observer 2 respectively. The automatic measurement overestimated the MLD slightly in the ilio-femoral artery at the average by 0.323mm (SD = 0.49mm, p < 0.001) compared to observer 1 and by 0.51mm (SD = 0.71mm, p < 0.001) compared to observer 2. The proposed segmentation approach can automatically provide reliable measurements of the entire arterial accessing route that can be used to support TAVR procedures. To the best of our knowledges, this approach is the first fully automatic segmentation method of the whole aorto-femoral vessel trajectory in CTA images.

IMPACT OF PRECISION OF LUMEN BOUNDARY EXTRACTED FROM CORONARY CT ON FFRCT: VALIDATION WITH OCT

The accuracy of fractional flow reserve derived from coronary CT (FFRCT) depends on the fidelity of the lumen boundary. It is unknown whether the lower spatial resolution of coronary CT compared to invasive imaging limits the accuracy of FFRCT or whether imprecision in minimum lumen area (MLA) at a

Isotropic 3D black blood MRI of abdominal aortic aneurysm wall and intraluminal thrombus

IntroductionThe aortic wall and intraluminal thrombus (ILT) have been increasingly studied as potential markers of progressive disease with abdominal aortic aneurysms (AAAs). Our goal was to develop a high resolution, 3D black blood MR technique for AAA wall and ILT imaging within a clinically acceptable scan time. MethodsTwenty two patients with AAAs (maximal diameter 4.3±1.0cm), along with five healthy volunteers, were imaged at 3T with a 3D T1-weighted fast-spin-echo sequence using variable flip angle trains (SPACE) with a preparation pulse (DANTE) for suppressing blood signal. Volunteers and ten patients were also scanned with SPACE alone for comparison purposes. The signal to noise ratio (SNR) and the aortic wall/ILT to lumen contrast to noise ratio (CNR) were measured. Qualitative image scores (1–4 scale) assessing the inner lumen and outer wall boundaries of AAA were performed by two blinded reviewers. In patients with ILT, the ratio of ILT signal intensity (ILTSI) over psoas muscle SI (MuscleSI) was calculated, and the signal heterogeneity of ILT was quantified as standard deviation (SD) over the mean. ResultsAll subjects were imaged successfully with an average scan time of 7.8±0.7minutes. The DANTE preparation pulse for blood suppression substantially reduced flow artifacts in SPACE with lower lumen SNR (8.8 vs. 21.4, p<0.001) and improved the wall/ILT to lumen CNR (9.9 vs. 6.3, p<0.001) in patients. Qualitative assessment showed improved visualization of lumen boundaries (73% higher scores on average, p=0.01) and comparable visualization of outer wall boundary (p>0.05). ILT was present in ten patients, with relatively high signal and a wide SD (average ILTSI/MuscleSI 1.42±0.48 (range 0.75–2.11)) and with SD/mean of 27.7%±6.6% (range 19.6%–39.4%). ConclusionHigh resolution, 3D black blood MRI of AAAs can be achieved in a clinical accepted scan time with reduction of flow artifacts using the DANTE preparation pulse. Signal characteristics of ILT can be quantified and may be used for improved patient-specific risk stratification.

TCT-333 Accuracy of lumen boundary extracted from coronary CTA for calcified and noncalcified plaques assessed using OCT data

Noninvasive methods to derive fractional flow reserve from coronary CT angiography data depend on the accuracy of the luminal boundary extracted from image data. The spatial resolution of coronary CTA data has been considered as a fundamental upper limit on the accuracy and precision of FFRCT, but

A semi-automated method for measuring the evolution of both lumen area and blood flow in carotid from Phase Contrast MRI

Phase-Contrast (PC) velocimetry Magnetic Resonance Imaging (MRI) is a useful modality to explore cardiovascular pathologies, but requires the automatic segmentation of vessels and the measurement of both lumen area and blood flow evolutions. In this paper, we propose a semi-automated method for extracting lumen boundaries of the carotid artery and compute both lumen area and blood flow evolutions over the cardiac cycle. This method uses narrow band region-based active contours in order to correctly capture the lumen boundary without being corrupted by surrounding structures. This approach is compared to traditional edge-based active contours, considered in related works, which significantly underestimate lumen area and blood flow. Experiments are performed using both a sequence of a homemade phantom and sequences of 20 real carotids, including a comparison with manual segmentation performed by a radiologist expert. Results obtained on the phantom sequence show that the edge-based approach leads to an underestimate of carotid lumen area and related flows of respectively 18.68% and 4.95%. This appears significantly larger than weak errors obtained using the region-based approach (respectively 2.73% and 1.23%). Benefits appear even better on the real sequences. The edge-based approach leads to underestimates of 40.88% for areas and 13.39% for blood flows, compared to limited errors of 7.41% and 4.6% with our method. Experiments also illustrate the high variability and therefore the lack of reliability of manual segmentation.

Abstract 509: Accurate Measurement of Carotid Lumen Diameter and Narrowing Utilizing Ultrasound

Introduction: Ultrasound is often used for monitoring of carotid disease. In current clinical practice, degree of stenosis is an important predictor to assess stroke risk. Lumen narrowing from plaque is currently measured via techniques such as computed tomographic scan, magnetic resonance angiogram or conventional angiogram. Duplex ultrasound measures degree of stenosis based on peak systolic velocities and other parameters and only provides a wide range of level of stenosis. Pursuing lumen size measurement in ultrasound via manual quantification of lumen diameter is tedious. Furthermore, non-uniformity in plaque growth makes it more challenging and time-consuming. There has been an increasing interest in the automatic and robust delineation of the lumen boundaries of the carotids and to measure the lumen diameter via ultrasound given its non-invasive and safe approach. Methods: Deidentified carotid ultrasound images were obtained on patients retrospectively who underwent carotid ultrasound at Toho University Ohashi Medical Center, Tokyo, Japan. A higher order derivative Gaussian filter is applied on these images to highlight the edges. Using pixel classification, lumen region is detected and lumen boundaries are estimated. Results: Of the 202 patients with common carotid artery images, 155 were males and 47 were females.Mean age 69 ± 15.9 years. Mean HbA1c, LDL, HDL and Cholesterol of patients were 6.28±1.1 mg/dl, 101.27±31.6 mg/dl, 50.26±14.8 mg/dl and 175.04±38 mg/dl, respectively. Specialist trained in carotid ultrasound manually traced lumen diameter. Automated tracing and lumen measurements were obtained. The coefficient of correlation between automated diameter and manual diameter was: 0.88, 0.91 and 0.93. The mean diameter error between automated and manual tracing were: 0.50±0.37 mm, 0.36±0.34 mm and 0.30±0.28 mm. Precision of merit between automated diameter and manual diameter was: 93.28%, 95.33% and 96.32% corresponding to manual tracers. Conclusions: The automated lumen diameter measurement is near real time, quick, accurate, fully automated and reliable to assess carotid lumen diameter and narrowing.

Automated measurement of stent strut coverage in intravascular optical coherence tomography

Optical coherence tomography (OCT) is a non-invasive, cross-sectional imaging modality that has become a prominent imaging method in percutaneous intracoronary intervention. We present an automated detection algorithm for stent strut coordinates and coverage in OCT images. The algorithm for stent strut detection is composed of a coordinate transformation from the polar to the Cartesian domains and application of second derivative operators in the radial and the circumferential directions. Local region-based active contouring was employed to detect lumen boundaries. We applied the method to the OCT pullback images acquired from human patients in vivo to quantitatively measure stent strut coverage. The validation studies against manual expert assessments demonstrated high Pearson’s coefficients (R = 0.99) in terms of the stent strut coordinates, with no significant bias. An averaged Hausdorff distance of < 120 μm was obtained for vessel border detection. Quantitative comparison in stent strut to vessel wall distance found a bias of < 12.3 μm and a 95% confidence of < 110 μm.

3D reconstruction of a carotid bifurcation from 2D transversal ultrasound images

Visualizing and analyzing the morphological structure of carotid bifurcations are important for understanding the etiology of carotid atherosclerosis, which is a major cause of stroke and transient ischemic attack. For delineation of vasculatures in the carotid artery, ultrasound examinations have been widely employed because of a noninvasive procedure without ionizing radiation. However, conventional 2D ultrasound imaging has technical limitations in observing the complicated 3D shapes and asymmetric vasodilation of bifurcations. This study aims to propose image-processing techniques for better 3D reconstruction of a carotid bifurcation in a rat by using 2D cross-sectional ultrasound images. A high-resolution ultrasound imaging system with a probe centered at 40MHz was employed to obtain 2D transversal images. The lumen boundaries in each transverse ultrasound image were detected by using three different techniques; an ellipse-fitting, a correlation mapping to visualize the decorrelation of blood flow, and the ellipse-fitting on the correlation map. When the results are compared, the third technique provides relatively good boundary extraction. The incomplete boundaries of arterial lumen caused by acoustic artifacts are somewhat resolved by adopting the correlation mapping and the distortion in the boundary detection near the bifurcation apex was largely reduced by using the ellipse-fitting technique. The 3D lumen geometry of a carotid artery was obtained by volumetric rendering of several 2D slices. For the 3D vasodilatation of the carotid bifurcation, lumen geometries at the contraction and expansion states were simultaneously depicted at various view angles. The present 3D reconstruction methods would be useful for efficient extraction and construction of the 3D lumen geometries of carotid bifurcations from 2D ultrasound images.