Estimation of noise in gray-scale and colored images using median absolute deviation (MAD)

This paper presents a new algorithm for estimation of noise (i.e., level of noise) in both gray-scale and color images (GSI, CI). The new technique is called median-absolute deviation (MAD). This technique does require an explicit estimation of the noise level or the signal to noise ratio (SNR), which is usually needed in most of the popular enhancement methods. Performance of the proposed method is evaluated on noisy images in real conditions and with artificial noise

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

Automatic detection of the end-diastolic and end-systolic from 4D echocardiographics images

Accurate detection of the End-Diastolic (ED) and End-Systolic (ES) frames of a cardiac cycle are significant factors that may affect the accuracy of abnormality assessment of a ventricle. This process is a routine step of the ventricle assessment procedure as most of the time in clinical reports many parameters are measured in these two frames to help in diagnosing and dissection making. According to the previous works the process of detecting the ED and ES remains a challenge in that the ED and ES frames for the cavity are usually determined manually by review of individual image phases of the cavity and/or tracking the tricuspid valve. The proposed algorithm aims to automatically determine the ED and ES frames from the four Dimensional Echocardiographic images (4DE) of the Right Ventricle (RV) from one cardiac cycle. By computing the area of three slices along one cardiac cycle and selecting the maximum area as the ED frame and the minimum area as the ES frame. This method gives an accurate determination for the ED and ES frames, hence avoid the need for time consuming, expert contributions during the process of computing the cavity stroke volume

3D surface reconstruction of coronary arteries from cardiovascular angiography to detect location of heart vessels

Complications and difficulties are common in the medical field. One of the important difficulties that a surgeon may face nowadays is that when a vessel or more vessels goes inside the surface of the heart. Coronary artery vessels naturally lie on the surface of the heart but sometimes a coronary artery vessel goes inside the heart muscle and stays there for awhile and then comes out again. In this case a surgeon will not be able to locate the artery during a bypass operation. Working on 2D projections can easily mislead the comprehension and the interpretation of the structures like in the case of stenosis quantification. Different acquisition techniques make it possible to obtain 3D models of the vessels network reconstructed from 2D angiographies. The problem is that the coronary angiograms can show the arteries through contrast dye projection but still cannot show the exact location of a coronary artery vessel. The proposed procedure to solve this problem in this thesis consists of three steps. The first step is the coronary artery trees extraction. We proposed an algorithm to extract tree vessels from cardiovascular angiography by removing the background and highlighting the coronary artery tree vessels. The second step is 3D reconstruction for coronary artery tree vessels. Since extracted vessels from step one will be in 2D which will offer little information to surgeons and is difficult to study as well, we need to reconstruct them in 3D to simplify their diagnosing and analyzing. The third step in the procedure is the surface fitting. The 3D model reconstructed from step two will offer more information about the coronary artery tree vessels but it will again be difficult to decide whether a vessel is in or out the heart’s surface. Therefore, we need to build a 3D surface out of the 3D cloud of points obtained from step two to simplify the detection of said vessels. To best confirm the location of a vessel and determine the depth of that vessel inside the heart, we added a step at the end of the research to measure the curvatures of the reconstructed surface and the maximum depth of a vessel inside that surface as well. This step will measure the depths of all curvatures and highlight the maximum. To surgeons, 1 cm (10 mm) depth of a vessel inside the heart could cause a problem during surgery; therefore, our approach would set out an alarm to warn the surgeon if that depth (10 mm) or more is present. We have tested the approach to raw of clinical data sets and the results show that our proposed approach is capable of detecting the location of vessels in about 98%. From those results we can conclude that our approach is robust and can act as a tool in surgery planning and scientific researches purposes