In the present study, a generalized active contour model of gradient vector flow is combined with the video techniques of Argus system to delineate and track sequential nearshore wave crest profiles in the shoaling pr...In the present study, a generalized active contour model of gradient vector flow is combined with the video techniques of Argus system to delineate and track sequential nearshore wave crest profiles in the shoaling process, up to their breaking on the shoreline. Previous applications of active contour models to water wave problems are limited to controllable wave tank experiments. By contrast, our application in this study is in a nearshore field environment where oblique images obtained under natural and varying condition of ambient light are employed. Existing Argus techniques produce plane image data or time series data from a selected small subset of discrete pixels. By contrast, the active contour model produces line image data along continuous visible curves such as wave crest profiles. The combination of these two existing techniques, the active contour model and Argus methodologies, facilitates the estimates of the direction wave field and phase speeds within the whole area covered by camera. These estimates are useful for the purpose of inverse calculation of the water depth. Applications of the present techniques to Hsi-tzu bay where a beach restoration program is currently undertaken are illustrated. This extension of Argus video techniques provides new application of optical remote sensing to study the hydrodynamics and morphology of a nearshore environment.展开更多
While executing tasks such as ocean pollution monitoring,maritime rescue,geographic mapping,and automatic navigation utilizing remote sensing images,the coastline feature should be determined.Traditional methods are n...While executing tasks such as ocean pollution monitoring,maritime rescue,geographic mapping,and automatic navigation utilizing remote sensing images,the coastline feature should be determined.Traditional methods are not satisfactory to extract coastline in high-resolution panchromatic remote sensing image.Active contour model,also called snakes,have proven useful for interactive specification of image contours,so it is used as an effective coastlines extraction technique.Firstly,coastlines are detected by water segmentation and boundary tracking,which are considered initial contours to be optimized through active contour model.As better energy functions are developed,the power assist of snakes becomes effective.New internal energy has been done to reduce problems caused by convergence to local minima,and new external energy can greatly enlarge the capture region around features of interest.After normalization processing,energies are iterated using greedy algorithm to accelerate convergence rate.The experimental results encompassed examples in images and demonstrated the capabilities and efficiencies of the improvement.展开更多
Liver hydatid disease is a common parasitic disease in farm and pastoral areas, which seriously influences people's health. Based on CT imaging features of this disease, an iterative approach for liver segmentatio...Liver hydatid disease is a common parasitic disease in farm and pastoral areas, which seriously influences people's health. Based on CT imaging features of this disease, an iterative approach for liver segmentation and hydatid lesion extraction simultaneously is proposed. In each iteration, our algorithm consists of two main steps: 1) according to the user-defined pixel seeds in the liver and hydatid lesion, Gaussian probability model fitting and smoothed Bayesian classification are applied to get initial segmentation of liver and lesion; 2) the parametric active contour model using priori shape force field is adopted to refine initial segmentation. We make subjective and objective evaluation on the proposed algorithm validity by the experiments of liver and hydatid lesion segmentation on different patients' CT slices. In comparison with ground-truth manual segmentation results, the experimental results show the effectiveness of our method to segment liver and hydatid lesion.展开更多
The measurement of thickness of material removed between serial sections is a crucial step of three-dimensional reconstruction. Active contour model is an efficient method for contour detection of objects on an image....The measurement of thickness of material removed between serial sections is a crucial step of three-dimensional reconstruction. Active contour model is an efficient method for contour detection of objects on an image. Based on the segmentation of the FeAl/ZrO2 composite image by using adaptive threshold, the gradient vector flow (GVF) snake was used to detect the contour of the indent. The horizontal diagonal length and the vertical diagonal length of the indent contour were acquired by measuring the distance from the uppermost snaxel to the lowermost snaxel and that from the leftmost snaxel to the rightmost snaxel respectively. Then the final diagonal length was gotten by averaging the vertical diagonal length and the horizontal diagonal length. The Vickers indenter was made by a square pyramidal-shaped diamond with opposite faces at an angle of 136°, so the geometrical relation was established between the thickness of material removed between two successive serial sections and the difference of diagonal length on the two serial sections. Based on the relation, the thickness of material removed between two successive serial sections was calculated using the two successive diagonals.展开更多
Traditional texture region location methods with Gabor features are often limited in the selection of Gabor filters and fail to deal with the target which contains both texture and non-texture parts.Thus,to solve this...Traditional texture region location methods with Gabor features are often limited in the selection of Gabor filters and fail to deal with the target which contains both texture and non-texture parts.Thus,to solve this problem,a two-step new model was proposed.In the first step,the original features extracted by Gabor filters are applied to training a self-organizing map(SOM) neural network and a novel merging scheme is presented to achieve the clustering.A back propagation(BP) network is used as a classifier to locate the target region approximately.In the second step,Chan-Vese active contour model is applied to detecting the boundary of the target region accurately and morphological processing is used to create a connected domain whose convex hull can cover the target region.In the experiments,the proposed method is demonstrated accurate and robust in localizing target on texture database and practical barcode location system as well.展开更多
A new scheme for femur shape recovery from volumetric images using deformable models was proposed. First, prior 3 D deformable femur models are created as templates using point distribution models technology. Second, ...A new scheme for femur shape recovery from volumetric images using deformable models was proposed. First, prior 3 D deformable femur models are created as templates using point distribution models technology. Second, active contour models are employed to segment the magnetic resonance imaging (MRI) volumetric images of the tibial and femoral joints and the deformable models are initialized based on the segmentation results. Finally, the objective function is minimized to give the optimal results constraining the surface of shapes.展开更多
One of the most complex tasks for computer-aided diagnosis(Intelligent decision support system)is the segmentation of lesions.Thus,this study proposes a new fully automated method for the segmentation of ovarian and b...One of the most complex tasks for computer-aided diagnosis(Intelligent decision support system)is the segmentation of lesions.Thus,this study proposes a new fully automated method for the segmentation of ovarian and breast ultrasound images.The main contributions of this research is the development of a novel Viola–James model capable of segmenting the ultrasound images of breast and ovarian cancer cases.In addition,proposed an approach that can efficiently generate region-of-interest(ROI)and new features that can be used in characterizing lesion boundaries.This study uses two databases in training and testing the proposed segmentation approach.The breast cancer database contains 250 images,while that of the ovarian tumor has 100 images obtained from several hospitals in Iraq.Results of the experiments showed that the proposed approach demonstrates better performance compared with those of other segmentation methods used for segmenting breast and ovarian ultrasound images.The segmentation result of the proposed system compared with the other existing techniques in the breast cancer data set was 78.8%.By contrast,the segmentation result of the proposed system in the ovarian tumor data set was 79.2%.In the classification results,we achieved 95.43%accuracy,92.20%sensitivity,and 97.5%specificity when we used the breast cancer data set.For the ovarian tumor data set,we achieved 94.84%accuracy,96.96%sensitivity,and 90.32%specificity.展开更多
In many practical applications of image segmentation problems,employing prior information can greatly improve segmentation results.This paper continues to study one kind of prior information,called prior distribution....In many practical applications of image segmentation problems,employing prior information can greatly improve segmentation results.This paper continues to study one kind of prior information,called prior distribution.Within this research,there is no exact template of the object;instead only several samples are given.The proposed method,called the parametric distribution prior model,extends our previous model by adding the training procedure to learn the prior distribution of the objects.Then this paper establishes the energy function of the active contour model(ACM)with consideration of this parametric form of prior distribution.Therefore,during the process of segmenting,the template can update itself while the contour evolves.Experiments are performed on the airplane data set.Experimental results demonstrate the potential of the proposed method that with the information of prior distribution,the segmentation effect and speed can be both improved efficaciously.展开更多
The growth patterns of mammary fat pads and glandular tissues inside the fat pads may be related with the risk factors of breast cancer.Quantitative measurements of this relationship are available after segmentation o...The growth patterns of mammary fat pads and glandular tissues inside the fat pads may be related with the risk factors of breast cancer.Quantitative measurements of this relationship are available after segmentation of mammary pads and glandular tissues.Rat fat pads may lose continuity along image sequences or adjoin similar intensity areas like epidermis and subcutaneous regions.A new approach for automatic tracing and segmentation of fat pads in magnetic resonance imaging(MRI) image sequences is presented,which does not require that the number of pads be constant or the spatial location of pads be adjacent among image slices.First,each image is decomposed into cartoon image and texture image based on cartoon-texture model.They will be used as smooth image and feature image for segmentation and for targeting pad seeds,respectively.Then,two-phase direct energy segmentation based on Chan-Vese active contour model is applied to partitioning the cartoon image into a set of regions,from which the pad boundary is traced iteratively from the pad seed.A tracing algorithm based on scanning order is proposed to accurately trace the pad boundary,which effectively removes the epidermis attached to the pad without any post processing as well as solves the problem of over-segmentation of some small holes inside the pad.The experimental results demonstrate the utility of this approach in accurate delineation of various numbers of mammary pads from several sets of MRI images.展开更多
基金supported by the Science Council,Taiwan,under Grant No.NSC95-2221-E-006-475-MY2
文摘In the present study, a generalized active contour model of gradient vector flow is combined with the video techniques of Argus system to delineate and track sequential nearshore wave crest profiles in the shoaling process, up to their breaking on the shoreline. Previous applications of active contour models to water wave problems are limited to controllable wave tank experiments. By contrast, our application in this study is in a nearshore field environment where oblique images obtained under natural and varying condition of ambient light are employed. Existing Argus techniques produce plane image data or time series data from a selected small subset of discrete pixels. By contrast, the active contour model produces line image data along continuous visible curves such as wave crest profiles. The combination of these two existing techniques, the active contour model and Argus methodologies, facilitates the estimates of the direction wave field and phase speeds within the whole area covered by camera. These estimates are useful for the purpose of inverse calculation of the water depth. Applications of the present techniques to Hsi-tzu bay where a beach restoration program is currently undertaken are illustrated. This extension of Argus video techniques provides new application of optical remote sensing to study the hydrodynamics and morphology of a nearshore environment.
基金Sponsoreds by the National Natural Science Foundation of China (Grant No. 60575016)
文摘While executing tasks such as ocean pollution monitoring,maritime rescue,geographic mapping,and automatic navigation utilizing remote sensing images,the coastline feature should be determined.Traditional methods are not satisfactory to extract coastline in high-resolution panchromatic remote sensing image.Active contour model,also called snakes,have proven useful for interactive specification of image contours,so it is used as an effective coastlines extraction technique.Firstly,coastlines are detected by water segmentation and boundary tracking,which are considered initial contours to be optimized through active contour model.As better energy functions are developed,the power assist of snakes becomes effective.New internal energy has been done to reduce problems caused by convergence to local minima,and new external energy can greatly enlarge the capture region around features of interest.After normalization processing,energies are iterated using greedy algorithm to accelerate convergence rate.The experimental results encompassed examples in images and demonstrated the capabilities and efficiencies of the improvement.
基金Science Special Fund for "Special Training" of Ethnical Minority Professional and Technical Intelligent in Xinjiang sponsored by the Scienceand Technology Department of Xinjiang Uygur Autonomous Regiongrant number:200723104+1 种基金National Natural Science Foundation of Chinagrant number:30960097
文摘Liver hydatid disease is a common parasitic disease in farm and pastoral areas, which seriously influences people's health. Based on CT imaging features of this disease, an iterative approach for liver segmentation and hydatid lesion extraction simultaneously is proposed. In each iteration, our algorithm consists of two main steps: 1) according to the user-defined pixel seeds in the liver and hydatid lesion, Gaussian probability model fitting and smoothed Bayesian classification are applied to get initial segmentation of liver and lesion; 2) the parametric active contour model using priori shape force field is adopted to refine initial segmentation. We make subjective and objective evaluation on the proposed algorithm validity by the experiments of liver and hydatid lesion segmentation on different patients' CT slices. In comparison with ground-truth manual segmentation results, the experimental results show the effectiveness of our method to segment liver and hydatid lesion.
基金Sponsored by the National Natural Science Foundation of China (Grant No.60873089)the Doctoral Fund of Shandong Province( Grant No.2007BS04018)
文摘The measurement of thickness of material removed between serial sections is a crucial step of three-dimensional reconstruction. Active contour model is an efficient method for contour detection of objects on an image. Based on the segmentation of the FeAl/ZrO2 composite image by using adaptive threshold, the gradient vector flow (GVF) snake was used to detect the contour of the indent. The horizontal diagonal length and the vertical diagonal length of the indent contour were acquired by measuring the distance from the uppermost snaxel to the lowermost snaxel and that from the leftmost snaxel to the rightmost snaxel respectively. Then the final diagonal length was gotten by averaging the vertical diagonal length and the horizontal diagonal length. The Vickers indenter was made by a square pyramidal-shaped diamond with opposite faces at an angle of 136°, so the geometrical relation was established between the thickness of material removed between two successive serial sections and the difference of diagonal length on the two serial sections. Based on the relation, the thickness of material removed between two successive serial sections was calculated using the two successive diagonals.
基金Supported by Tianjin Natural Science Fundation (No.07JCZDJC05800)
文摘Traditional texture region location methods with Gabor features are often limited in the selection of Gabor filters and fail to deal with the target which contains both texture and non-texture parts.Thus,to solve this problem,a two-step new model was proposed.In the first step,the original features extracted by Gabor filters are applied to training a self-organizing map(SOM) neural network and a novel merging scheme is presented to achieve the clustering.A back propagation(BP) network is used as a classifier to locate the target region approximately.In the second step,Chan-Vese active contour model is applied to detecting the boundary of the target region accurately and morphological processing is used to create a connected domain whose convex hull can cover the target region.In the experiments,the proposed method is demonstrated accurate and robust in localizing target on texture database and practical barcode location system as well.
基金National Natural Science Foundation ofChina!( 69772 0 0 2 )
文摘A new scheme for femur shape recovery from volumetric images using deformable models was proposed. First, prior 3 D deformable femur models are created as templates using point distribution models technology. Second, active contour models are employed to segment the magnetic resonance imaging (MRI) volumetric images of the tibial and femoral joints and the deformable models are initialized based on the segmentation results. Finally, the objective function is minimized to give the optimal results constraining the surface of shapes.
文摘One of the most complex tasks for computer-aided diagnosis(Intelligent decision support system)is the segmentation of lesions.Thus,this study proposes a new fully automated method for the segmentation of ovarian and breast ultrasound images.The main contributions of this research is the development of a novel Viola–James model capable of segmenting the ultrasound images of breast and ovarian cancer cases.In addition,proposed an approach that can efficiently generate region-of-interest(ROI)and new features that can be used in characterizing lesion boundaries.This study uses two databases in training and testing the proposed segmentation approach.The breast cancer database contains 250 images,while that of the ovarian tumor has 100 images obtained from several hospitals in Iraq.Results of the experiments showed that the proposed approach demonstrates better performance compared with those of other segmentation methods used for segmenting breast and ovarian ultrasound images.The segmentation result of the proposed system compared with the other existing techniques in the breast cancer data set was 78.8%.By contrast,the segmentation result of the proposed system in the ovarian tumor data set was 79.2%.In the classification results,we achieved 95.43%accuracy,92.20%sensitivity,and 97.5%specificity when we used the breast cancer data set.For the ovarian tumor data set,we achieved 94.84%accuracy,96.96%sensitivity,and 90.32%specificity.
基金supported by the National Key R&D Program of China(2018YFC0309400)the National Natural Science Foundation of China(61871188)
文摘In many practical applications of image segmentation problems,employing prior information can greatly improve segmentation results.This paper continues to study one kind of prior information,called prior distribution.Within this research,there is no exact template of the object;instead only several samples are given.The proposed method,called the parametric distribution prior model,extends our previous model by adding the training procedure to learn the prior distribution of the objects.Then this paper establishes the energy function of the active contour model(ACM)with consideration of this parametric form of prior distribution.Therefore,during the process of segmenting,the template can update itself while the contour evolves.Experiments are performed on the airplane data set.Experimental results demonstrate the potential of the proposed method that with the information of prior distribution,the segmentation effect and speed can be both improved efficaciously.
基金Supported by National Basic Research Program of China (No.2003CB716103)partially supported by the US Army Breast Cancer Research Program (DAMD17-03-1-0446)
文摘The growth patterns of mammary fat pads and glandular tissues inside the fat pads may be related with the risk factors of breast cancer.Quantitative measurements of this relationship are available after segmentation of mammary pads and glandular tissues.Rat fat pads may lose continuity along image sequences or adjoin similar intensity areas like epidermis and subcutaneous regions.A new approach for automatic tracing and segmentation of fat pads in magnetic resonance imaging(MRI) image sequences is presented,which does not require that the number of pads be constant or the spatial location of pads be adjacent among image slices.First,each image is decomposed into cartoon image and texture image based on cartoon-texture model.They will be used as smooth image and feature image for segmentation and for targeting pad seeds,respectively.Then,two-phase direct energy segmentation based on Chan-Vese active contour model is applied to partitioning the cartoon image into a set of regions,from which the pad boundary is traced iteratively from the pad seed.A tracing algorithm based on scanning order is proposed to accurately trace the pad boundary,which effectively removes the epidermis attached to the pad without any post processing as well as solves the problem of over-segmentation of some small holes inside the pad.The experimental results demonstrate the utility of this approach in accurate delineation of various numbers of mammary pads from several sets of MRI images.