Retinal layer segmentation using gradient feature calculation in OCT

Retinal diseases pose significant challenges to global healthcare systems,necessitating accurate and efficient diagnostic methods.Optical Coherence Tomography(OCT)has emerged as a valuable tool for diagnosing and monitoring retinal conditions due to its noncontact and noninvasive nature.This paper presents a novel retinal layering method based on OCT images,aimed at enhancing the accuracy of retinal lesion diagnosis.The method utilizes gradient analysis to effectively identify and segment retinal layers.By selecting a column of pixels as a segmentation line and utilizing gradient information from adjacent pixels,the method initiates and proceeds with the layering process.This approach addresses potential issues arising from partial layer overlapping,minimizing deviations in layer segmentation.Experimental results demonstrate the efficacy of the proposed method in accurately segmenting eight retinal boundaries,with an average absolute position deviation of 1.75 pixels.By providing accurate segmentation of retinal layers,this approach contributes to the early detection and management of ocular conditions,ultimately improving patient outcomes and reducing the global burden of vision-related ailments.

Automated retinal layer segmentation in optical coherence tomography images with intraretinal fluid

We propose a novel retinal layer segmentation method to accurately segment 10 retinal layers in optical coherence tomography(OCT)images with intraretinal fluid.The method used a fan filter to enhance the linear information pertaining to retinal boundaries in an OCT image by reducing the effect of vessel shadows and fluid regions.A random forest classifier was employed to predict the location of the boundaries.Two novel methods of boundary redirection(SR)and similarity correction(SC)were combined to carry out boundary tracking and thereby accurately locate retinal layer boundaries.Experiments were performed on healthy controls and subjects with diabetic macular edema(DME).The proposed method required an average of 415 s for healthy controls and of 482 s for subjects with DME and achieved high accuracy for both groups of subjects.The proposed method requires a shorter running time than previous methods and also provides high accuracy.Thus,the proposed method may be a better choice for small training datasets.

3D automatic segmentation method for retinal optical coherence tomography volume data using boundary surface enhancement

With the introduction of spectral-domain optical coherence tomography(SD-OCT),much larger image datasets are routinely acquired compared to what was possible using the previous generation of time-domain OCT.Thus,there is a critical need for the development of three-dimensional(3D)segmentation methods for processing these data.We present here a novel 3D automatic segmentation method for retinal OCT volume data.Brie°y,to segment a boundary surface,two OCT volume datasets are obtained by using a 3D smoothingfilter and a 3D differentialfilter.Their linear combination is then calculated to generate new volume data with an enhanced boundary surface,where pixel intensity,boundary position information,and intensity changes on both sides of the boundary surface are used simultaneously.Next,preliminary discrete boundary points are detected from the A-Scans of the volume data.Finally,surface smoothness constraints and a dynamic threshold are applied to obtain a smoothed boundary surface by correcting a small number of error points.Our method can extract retinal layer boundary surfaces sequentially with a decreasing search region of volume data.We performed automatic segmentation on eight human OCT volume datasets acquired from a commercial Spectralis OCT system,where each volume of datasets contains 97 OCT B-Scan images with a resolution of 496
512(each B-Scan comprising 512 A-Scans containing 496 pixels);experimental results show that this method can accurately segment seven layer boundary surfaces in normal as well as some abnormal eyes.

Video segmentation using Maximum Entropy Model

Detecting objects of interest from a video sequence is a fundamental and critical task in automated visual surveillance. Most current approaches only focus on discriminating moving objects by background subtraction whether or not the objects of interest can be moving or stationary. In this paper, we propose layers segmentation to detect both moving and stationary target objects from surveillance video. We extend the Maximum Entropy (ME) statistical model to segment layers with features, which are collected by constructing a codebook with a set of codewords for each pixel. We also indicate how the training models are used for the discrimination of target objects in surveillance video. Our experimental results are presented in terms of the success rate and the segmenting precision.

Research on a New Type of Diamond Saw Plate

With the developing of stone material, diamond saw pl ate is used widely, and in order to increase cutting efficiency and life-span o f diamond saw plate, there are a lot of research jobs of segment for diamond saw plate. Layered segment for diamond saw plate is to divide single segment into s everal cutting tools by its structure, then increases rock-cutting faces. For i mpregnated man-made diamond saw plate, the bonding strength of diamonds with ma trix material has great effect on its life and service. Diamond is a kind of non metal and there is such high interface energy between diamond and common metals or alloys that diamond surface can’t be soaked by low melt-point metal or allo y. Diamonds are hold in metal matrix of working layer only mechanically, rather than bonded chemically, so the usage rate of diamonds in working layer is very l ow. Weakly impregnated method refers to covering diamonds with a thin layer of tu ngsten carbide mechanically by physical method, and chemical plating membrane re fers to coating a layer of carbide, which can react with the carbon atoms on the surface of diamond by chemical method and be soaked by matrix metal. In this pa per it analyses working mechanism and sintering process of layered segment of di amond saw plate by means of resistor hot-pressing sintering, it points out shor tages of layered structure, and raises using weakly impregnated layer instead of pure matrix layer, then overcomes the pure matrix layer slipping by pulling out diamonds earlier to improve cutting efficiency of saw plate, in the same time u ses diamond grains of chemical plating membrane proposed then preventing the hea t-hurting to diamond grains in working layer during the process of welding and sintering and improving the bonding strength of diamond with matrix, then improv ing life-span and aging of diamond saw. The theory of the design of mixed holding of diamonds by matrix of saw plate assures that chemical plating diamonds in working layer cut rock and weakly impr egnated diamonds in weakly impregnated layer make segment expose, then design a new type of layered segment for diamond saw plate.

Seismic and vibration control of segmented isolation layer in underground structure-diaphragm wall system

In this paper,a seismic and vibration reduction measure of subway station is developed by setting a segmented isolation layer between the sidewall of structure and the diaphragm wall.The segmented isolation layer consists of a rigid layer and a flexible layer.The rigid layer is installed at the joint section between the structural sidewall and slab,and the flexible layer is installed at the remaining sections.A diaphragm wall-segmented isolation layer-subway station structure system is constructed.Seismic and vibration control performance of the diaphragm wall-segmented isolation layer-subway station structure system is evaluated by the detailed numerical analysis.Firstly,a three-dimensional nonlinear time-history analysis is carried out to study the seismic response of the station structure by considering the effect of different earthquake motions and stiffness of segmented isolation layer.Subsequently,the vibration response of site under training loading is also studied by considering the influence of different train velocities and stiffness of the segmented isolation layer.Numerical results demonstrate that the diaphragm wall-segmented isolation layer-subway station structure system can not only effectively reduce the lateral deformation of station structure,but also reduce the tensile damage of the roof slab.On the other hand,the developed reduction measure can also significantly reduce the vertical peak displacements of site under training loading.

Hybrid vibration isolation optimization of a flexible manipulator based on neural network agent model

Segmented Active Constrained Layer Damping(SACLD)is an intelligent vibration-damping structure,which could be applied to the sectors of aviation,aerospace,and transportation engineering to reduce the vibration of flexible structures.Moreover,machine learning technology is widely used in the engineering field because of its efficient multi-objective optimization.The dynamic simulation of a rotational segmental flexible manipulator system is presented,in which enhanced active constrained layer damping is carried out,and the neural network model of Genetic Algorithm-Back Propagation(GA-BP)algorithm is investigated.Vibration suppression and structural optimization of the SACLD manipulator model are studied based on vibration mode and damping prediction.The modal responses of the SACLD manipulator model at rest and rotation are obtained.In addition,the four model indices are optimized using the GA-BP neural network:axial incision size,axial incision position,circumferential incision size,and circumferential incision position.Finally,the best model for vibration suppression is obtained.