Reconstruction of Three-Dimensional Blood Vessel Model Using Fractal Interpolation

Fractal method is used in the image processing and studying the irregular and the complex shapes in the image. It is also used in the reconstruction and smoothing of one-, two-, and three-dimensional data. In this chapter, we present an interpolating fractal algorithm to reconstruct 3D blood vessels. Firstly, the proposed method determines the blood vessel centerline from the 2D retina image, and then it uses the Douglas-Peucker algorithm to detect the control points. Secondly, we use the 3D fractal interpolation and iterated function systems for the visualization and reconstruction of these blood vessels. The results showed that the obtained reduction rate is between 71 and 94% depending on the tolerance value. The 3D blood vessels model can be reconstructed efficiently by using the 3D fractal interpolation method

New insights into the lymphovascular microanatomy of the colon and the risk of metastases in pT1 colorectal cancer obtained with quantitative methods and three-dimensional digital reconstruction

Aims: UK faecal occult blood test screening has tripled the proportion of pT1 colorectal cancers. The risk of metastasis is predicted by depth of invasion, suggesting that access to deep lymphovascular vessels is important. The aim of this study was to quantify the distribution and size of the submucosal vasculature, and generate a novel three-dimensional (3D) model to validate the findings. Methods and results: Thirty samples of normal large bowel wall were immunostained with CD31, a vascular endothelium marker, to identify blood vessels, which were quantified and digitally analysed for their number, circumference, area and diameter in the deep mucosa and submucosa (Sm1, Sm2, and Sm3). The model required serial sections, a double immunostain (using CD31 and D2-40), and 3D reconstruction. Significant differences were shown between submucosal layers in the number, circumference and area of vessels (P < 0.001). Blood vessels were most numerous in the mucosa (11.79 vessels/0.2 mm2) but smaller [median area of 247 μm2, interquartile range (IQR) 162–373 μm2] than in Sm2, where they were fewer in number (6.92 vessels/0.2 mm2) but considerably larger (2086 μm2, IQR 1007–4784 μm2). The 3D model generated novel observations on lymphovascular structures. Conclusions: The number and size of blood vessels do not increase with depth of submucosa, as hypothesized. The distribution of vessels suggests that we should investigate the area or volume of submucosal invasion rather than the depth

Development of a real-time high-resolution 3D ultrasound imaging system

In this work a real-time high-resolution 3D ultrasound imaging system is developed, allowing the 3D acquisition and imaging of high-resolution ultrasound data for biomedical applications. The system uses ultrasound transducers in the ranges of 30 to 100 MHz, and allows full access of the radiofrequency (RF) ultrasound data for the 3D image reconstruction. This work includes the development of two graphical user interfaces in C++ to interact with a high-resolution ultrasound system and to image the high-resolution ultrasound data. In addition, a methodology is described and implemented in the system for 3D ultrasound reconstruction and visualization. The development of these GUIs allows easy 3D high-resolution ultrasound acquisition and imaging to any user with basic knowledge in ultrasound and with only minimal and faster training in the system and the GUIs. This capability opens the system to any researcher or person interested in performing experimentations with high-resolution ultrasound.;The high-resolution 3D ultrasound imaging system is tested to assess atherosclerosis using different mouse models. To assess atherosclerosis, a series of in vitro studies are performed to 3D scan vessels of mouse aortas and carotids vessels with atherosclerosis, as well as mouse hearts with atherosclerosis. The apolipoprotein E-knockout (APOE) and the apolipoprotein E-A1 adenosine receptor double knockout (DKO) mice model with their wild type control (C57) are used. Three-dimensional reconstructions were rendered showing good matches with the samples morphology. In addition, 3D sections of the data are reconstructed showing atherosclerotic plaque in the samples. The 3D ultrasound reconstruction allows for us to analyze a sample from outside and inside by rotating around any angle and cropping non-relevant data, allowing us to observe shape and appearance of the 3D structures. Finally, after reconstructing and analyzing the 3D ultrasound images, a 3D quantitative assessment of atherosclerotic plaque is performed. After analyzing the samples, the plaque lesions of DKO mouse model exhibits smaller areas than those of the APOE mouse model. Additionally, the C57 mouse model is clean of any atherosclerosis. These findings are in agreement with a previous study of our group for these mouse models

Three-dimensional reconstruction of myocardial contrast perfusion from biplane cineangiograms by means of linear programming techniques

The assessment of coronary flow reserve from the instantaneous distribution of the contrast agent within the coronary vessels and myocardial muscle at the control state and at maximal flow has been limited by the superimposition of myocardial regions of interest in the two-dimensional images. To overcome these limitations, we are in the process of developing a three-dimensional (3D) reconstruction technique to compute the contrast distribution in cross sections of the myocardial muscle from two orthogonal cineangiograms. To limit the number of feasible solutions in the 3D-reconstruction space, the 3D-geometry of the endo- and epicardial boundaries of the myocardium must be determined. For the geometric reconstruction of the epicardium, the centerlines of the left coronary arterial tree are manually or automatically traced in the biplane views. Next, the bifurcations are detected automatically and matched in these two views, allowing a 3D-representation of the coronary tree. Finally, the circumference of the left ventricular myocardium in a selected cross section can be computed from the intersection points of this cross section with the 3D coronary tree using B-splines. For the geometric reconstruction of the left ventricular cavity, we envision to apply the elliptical approximation technique using the LV boundaries defined in the two orthogonal views, or by applying more complex 3D-reconstruction techniques including densitometry. The actual 3D-reconstruction of the contrast distribution in the myocardium is based on a linear programming technique (Transportation model) using cost coefficient matrices. Such a cost coefficient matrix must contain a maximum amount of a priori information, provided by a computer generated model and updated with actual data from the angiographic views. We have only begun to solve this complex problem. However, based on our first experimental results we expect that the linear programming approach with advanced cost coefficient matrices and computed model will lead to a

Specular reflection removal and bloodless vessel segmentation for 3-D heart model reconstruction from single view images

Three Dimensional (3D) human heart model is attracting attention for its role in medical images for education and clinical purposes. Analysing 2D images to obtain meaningful information requires a certain level of expertise. Moreover, it is time consuming and requires special devices to obtain aforementioned images. In contrary, a 3D model conveys much more information. 3D human heart model reconstruction from medical imaging devices requires several input images, while reconstruction from a single view image is challenging due to the colour property of the heart image, light reflections, and its featureless surface. Lights and illumination condition of the operating room cause specular reflections on the wet heart surface that result in noises forming of the reconstruction process. Image-based technique is used for the proposed human heart surface reconstruction. It is important the reflection is eliminated to allow for proper 3D reconstruction and avoid imperfect final output. Specular reflections detection and correction process examine the surface properties. This was implemented as a first step to detect reflections using the standard deviation of RGB colour channel and the maximum value of blue channel to establish colour, devoid of specularities. The result shows the accurate and efficient performance of the specularities removing process with 88.7% similarity with the ground truth. Realistic 3D heart model reconstruction was developed based on extraction of pixel information from digital images to allow novice surgeons to reduce the time for cardiac surgery training and enhancing their perception of the Operating Theatre (OT). Cardiac medical imaging devices such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) images, or Echocardiography provide cardiac information. However,these images from medical modalities are not adequate, to precisely simulate the real environment and to be used in the training simulator for cardiac surgery. The propose method exploits and develops techniques based on analysing real coloured images taken during cardiac surgery in order to obtain meaningful information of the heart anatomical structures. Another issue is the different human heart surface vessels. The most important vessel region is the bloodless, lack of blood, vessels. Surgeon faces some difficulties in locating the bloodless vessel region during surgery. The thesis suggests a technique of identifying the vessels’ Region of Interest (ROI) to avoid surgical injuries by examining an enhanced input image. The proposed method locates vessels’ ROI by using Decorrelation Stretch technique. This Decorrelation Stretch can clearly enhance the heart’s surface image. Through this enhancement, the surgeon become enables effectively identifying the vessels ROI to perform the surgery from textured and coloured surface images. In addition, after enhancement and segmentation of the vessels ROI, a 3D reconstruction of this ROI takes place and then visualize it over the 3D heart model. Experiments for each phase in the research framework were qualitatively and quantitatively evaluated. Two hundred and thirteen real human heart images are the dataset collected during cardiac surgery using a digital camera. The experimental results of the proposed methods were compared with manual hand-labelling ground truth data. The cost reduction of false positive and false negative of specular detection and correction processes of the proposed method was less than 24% compared to other methods. In addition, the efficient results of Root Mean Square Error (RMSE) to measure the correctness of the z-axis values to reconstruction of the 3D model accurately compared to other method. Finally, the 94.42% accuracy rate of the proposed vessels segmentation method using RGB colour space achieved is comparable to other colour spaces. Experimental results show that there is significant efficiency and robustness compared to existing state of the art methods

Three dimension reconstruction of coronary artery tree using single-view cineangiogram

Whereas most of the conventional techniques propose using multiview cineangiograms to reconstruct 3D objects this article proposes to integrate a Three Dimension(3D) model of the coronary artery tree using a standard single-view cineangiogram. Splitting the cineangiograms into non-sequenced and different angle views is how the data is supplied in this method. Each single view can be used to reconstruct a robust 3D model of the coronary artery from that angle of view. Although the dynamic variations of blood vessels curvature have been difficult to study in Two Dimension (2D) angiograms, there is both experimental and clinical evidence showing that 3D coronary reconstruction is very useful for surgery planning and clinical study. Approach: The algorithm has three stages. The first stage is the vessel extraction and labeling for each view for the purpose of constructing the 3D model, while in the second stage, the vessels information (x, y and z) will be saved in a data file to be forwarded to the next stage. Finally, we input the x, y and z of a specific coronary artery tree to the OPENGL library included in the software, which we developed and called Fast 3D (F3D) and which is displayed in R3. Results: Experimental evaluation has been done to clinical raw data sets where the experimental results revealed that the proposed algorithm has a robust 3D output. Conclusion: Results showed that our proposed algorithm has high robustness for a variety of image resolutions and voxel anisotropy

Hepatic Vessel Segmentation for 3D Planning of Liver Surgery

none8Rationale and Objectives: The aim of this study was to identify the optimal parameter configuration of a new algorithm for fully automatic segmentation of hepatic vessels, evaluating its accuracy in view of its use in a computer system for three-dimensional (3D) planning of liver surgery. Materials and Methods: A phantom reproduction of a human liver with vessels up to the fourth subsegment order, corresponding to a minimum diameter of 0.2 mm, was realized through stereolithography, exploiting a 3D model derived from a real human computed tomographic data set. Algorithm parameter configuration was experimentally optimized, and the maximum achievable segmentation accuracy was quantified for both single two-dimensional slices and 3D reconstruction of the vessel network, through an analytic comparison of the automatic segmentation performed on contrast-enhanced computed tomographic phantom images with actual model features. Results: The optimal algorithm configuration resulted in a vessel detection sensitivity of 100% for vessels > 1 mm in diameter, 50% in the range 0.5 to 1 mm, and 14% in the range 0.2 to 0.5 mm. An average area overlap of 94.9% was obtained between automatically and manually segmented vessel sections, with an average difference of 0.06 mm2. The average values of corresponding false-positive and false-negative ratios were 7.7% and 2.3%, respectively. Conclusions: A robust and accurate algorithm for automatic extraction of the hepatic vessel tree from contrast-enhanced computed tomographic volume images was proposed and experimentally assessed on a liver model, showing unprecedented sensitivity in vessel delineation. This automatic segmentation algorithm is promising for supporting liver surgery planning and for guiding intraoperative resections.Francesco Conversano;Roberto Franchini;Christian Demitri;Laurent Massoptier;Francesco Montagna;Alfonso Maffezzoli;Antonio Malvasi;Sergio CasciaroFrancesco, Conversano; Roberto, Franchini; Demitri, Christian; Laurent, Massoptier; Francesco, Montagna; Maffezzoli, Alfonso; Antonio, Malvasi; Sergio, Casciar

3D reconstruction of cerebral blood flow and vessel morphology from x-ray rotational angiography

Three-dimensional (3D) information on blood flow and vessel morphology is important when assessing cerebrovascular disease and when monitoring interventions. Rotational angiography is nowadays routinely used to determine the geometry of the cerebral vasculature. To this end, contrast agent is injected into one of the supplying arteries and the x-ray system rotates around the head of the patient while it acquires a sequence of x-ray images. Besides information on the 3D geometry, this sequence also contains information on blood flow, as it is possible to observe how the contrast agent is transported by the blood. The main goal of this thesis is to exploit this information for the quantitative analysis of blood flow. I propose a model-based method, called flow map fitting, which determines the blood flow waveform and the mean volumetric flow rate in the large cerebral arteries. The method uses a model of contrast agent transport to determine the flow parameters from the spatio-temporal progression of the contrast agent concentration, represented by a flow map. Furthermore, it overcomes artefacts due to the rotation (overlapping vessels and foreshortened vessels at some projection angles) of the c-arm using a reliability map. For the flow quantification, small changes to the clinical protocol of rotational angiography are desirable. These, however, hamper the standard 3D reconstruction. Therefore, a new method for the 3D reconstruction of the vessel morphology which is tailored to this application is also presented. To the best of my knowledge, I have presented the first quantitative results for blood flow quantification from rotational angiography. Additionally, the model-based approach overcomes several problems which are known from flow quantification methods for planar angiography. The method was mainly validated on images from different phantom experiments. In most cases, the relative error was between 5% and 10% for the volumetric mean flow rate and between 10% and 15% for the blood flow waveform. Additionally, the applicability of the flow model was shown on clinical images from planar angiographic acquisitions. From this, I conclude that the method has the potential to give quantitative estimates of blood flow parameters during cerebrovascular interventions