Pub Date : 1996-06-21DOI: 10.1109/MMBIA.1996.534075
Zsofia Tari, J. Shah, H. Pien
In recent years, curve evolution has been applied to smoothing of shapes and shape analysis with considerable success, especially in biomedical image analysis. The multiscale analysis provides information regarding parts of shapes, their axes or centers and shape skeletons. Here, the authors show that the level sets of an edge-strength function provide essentially the same shape analysis as provided by curve evolution. The new method has several advantages over the method of curve evolution. Since the governing equation is linear, the implementation is simpler and faster. The same equation applies to problems of higher dimension. An important advantage is that unlike the method of curve evolution, the new method is applicable to shapes which may have junctions such as triple points. The edge-strength may be calculated from raw images without first extracting the shape outline. Thus the method can be applied to raw images. The method provides a way to approach the segmentation problem and shape analysis within a common integrated framework.
{"title":"A computationally efficient shape analysis via level sets","authors":"Zsofia Tari, J. Shah, H. Pien","doi":"10.1109/MMBIA.1996.534075","DOIUrl":"https://doi.org/10.1109/MMBIA.1996.534075","url":null,"abstract":"In recent years, curve evolution has been applied to smoothing of shapes and shape analysis with considerable success, especially in biomedical image analysis. The multiscale analysis provides information regarding parts of shapes, their axes or centers and shape skeletons. Here, the authors show that the level sets of an edge-strength function provide essentially the same shape analysis as provided by curve evolution. The new method has several advantages over the method of curve evolution. Since the governing equation is linear, the implementation is simpler and faster. The same equation applies to problems of higher dimension. An important advantage is that unlike the method of curve evolution, the new method is applicable to shapes which may have junctions such as triple points. The edge-strength may be calculated from raw images without first extracting the shape outline. Thus the method can be applied to raw images. The method provides a way to approach the segmentation problem and shape analysis within a common integrated framework.","PeriodicalId":436387,"journal":{"name":"Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116937426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1996-06-21DOI: 10.1109/MMBIA.1996.534074
D.C. Wilson, E. Geiser, D. Conetta, J. Murphy, Dongxing Wang
The purpose of this report is to present a brief overview of a computer-based method designed to automatically approximate the epicardial and endocardial borders of the heart for echocardiographic images acquired from the parasternal transthoracic short-axis view. The only user input required is the end diastolic (ED) and end systolic (ES) frame numbers. The method was tested off-line on a developmental database acquired retrospectively from 55 patient studies (2 cycles/patient). The measurements provided by the computer-based method were comparable to those made by 3 expert observers.
{"title":"An automated algorithm for analysis of 2-D echocardiographic short-axis images: a brief overview","authors":"D.C. Wilson, E. Geiser, D. Conetta, J. Murphy, Dongxing Wang","doi":"10.1109/MMBIA.1996.534074","DOIUrl":"https://doi.org/10.1109/MMBIA.1996.534074","url":null,"abstract":"The purpose of this report is to present a brief overview of a computer-based method designed to automatically approximate the epicardial and endocardial borders of the heart for echocardiographic images acquired from the parasternal transthoracic short-axis view. The only user input required is the end diastolic (ED) and end systolic (ES) frame numbers. The method was tested off-line on a developmental database acquired retrospectively from 55 patient studies (2 cycles/patient). The measurements provided by the computer-based method were comparable to those made by 3 expert observers.","PeriodicalId":436387,"journal":{"name":"Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129720499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1996-06-21DOI: 10.1109/MMBIA.1996.534084
J. F. Mangin, J. Régis, V. Frouin
Proposes an alternative to mathematical morphology to analyze complex shapes. This approach aims mainly at the detection of shape bottlenecks which are often of interest in medical imaging because of their anatomical meaning. The detection idea consists in simulating the steady state of an information transmission process between two parts of a complex object in order to highlight bottlenecks as areas of high information flow. This information transmission process is supposed to have a conservative flow which leads to the well-known Dirichlet-Neumann problem. This problem is solved using finite differences, over-relaxation and a raw to fine implementation. The method is applied to the detection of main bottlenecks of brain white matter network, namely corpus callosum, anterior commissure and brain stem.
{"title":"Shape bottlenecks and conservative flow systems [medical image analysis]","authors":"J. F. Mangin, J. Régis, V. Frouin","doi":"10.1109/MMBIA.1996.534084","DOIUrl":"https://doi.org/10.1109/MMBIA.1996.534084","url":null,"abstract":"Proposes an alternative to mathematical morphology to analyze complex shapes. This approach aims mainly at the detection of shape bottlenecks which are often of interest in medical imaging because of their anatomical meaning. The detection idea consists in simulating the steady state of an information transmission process between two parts of a complex object in order to highlight bottlenecks as areas of high information flow. This information transmission process is supposed to have a conservative flow which leads to the well-known Dirichlet-Neumann problem. This problem is solved using finite differences, over-relaxation and a raw to fine implementation. The method is applied to the detection of main bottlenecks of brain white matter network, namely corpus callosum, anterior commissure and brain stem.","PeriodicalId":436387,"journal":{"name":"Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114622045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1996-06-21DOI: 10.1109/MMBIA.1996.534062
J. Little, D. Hill, D. Hawkes
Medical image registration can provide useful clinical information by relating images of the same patient acquired from different modalities, or from serial studies with a single modality. Current algorithms invariably assume that the objects in the images can be treated as a rigid body. In practice, some parts of a patient, usually bony structures, may move as rigid bodies while others may deform. To address this, the authors have developed a new technique that allows identified objects in the image to move as rigid bodies, while the remainder smoothly deforms. Euclidean distance transforms calculated from the rigid objects are used to weight a linear combination of pre-defined linear transformations, one for each rigid body in the image, and also to form a modified radial basis function. This ensures that the non-linear deformation tends to zero as one moves towards the rigid body boundary. The resulting deformation technique is valid in any dimension, subject to the choice of the basis function. The authors demonstrate this technique in two dimensions on a pattern of rigid square structures to simulate the vertebral bodies of the spine, and on sagittal magnetic resonance images collected from a volunteer.
{"title":"Deformations incorporating rigid structures [medical imaging]","authors":"J. Little, D. Hill, D. Hawkes","doi":"10.1109/MMBIA.1996.534062","DOIUrl":"https://doi.org/10.1109/MMBIA.1996.534062","url":null,"abstract":"Medical image registration can provide useful clinical information by relating images of the same patient acquired from different modalities, or from serial studies with a single modality. Current algorithms invariably assume that the objects in the images can be treated as a rigid body. In practice, some parts of a patient, usually bony structures, may move as rigid bodies while others may deform. To address this, the authors have developed a new technique that allows identified objects in the image to move as rigid bodies, while the remainder smoothly deforms. Euclidean distance transforms calculated from the rigid objects are used to weight a linear combination of pre-defined linear transformations, one for each rigid body in the image, and also to form a modified radial basis function. This ensures that the non-linear deformation tends to zero as one moves towards the rigid body boundary. The resulting deformation technique is valid in any dimension, subject to the choice of the basis function. The authors demonstrate this technique in two dimensions on a pattern of rigid square structures to simulate the vertebral bodies of the spine, and on sagittal magnetic resonance images collected from a volunteer.","PeriodicalId":436387,"journal":{"name":"Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127960244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1996-06-21DOI: 10.1109/MMBIA.1996.534078
W. Niessen, K. Vincken, M. Viergever
Different multiscale generators are qualitatively compared with respect to their performance within a multiscale linking model for image segmentation. The linking model used is the hyperstack that was inspired by linear scale space theory. The authors discuss which properties of this paradigm are essential to determine which multiscale representations are suited as input to the hyperstack. If selected, one of the main problems the authors tackle is the estimation of the local scale such that the various stacks of images can effectively be compared. For nonlinear multiscale representations, which cart be written as modified diffusion equations, an upper bound can be achieved by synchronizing the evolution parameter. The synchronization is empirically verified by counting the number of elliptic patches at corresponding scales. The authors compare the resulting stacks of images and the segmentation on a test image and a coronal MR brain image.
{"title":"Comparison of multiscale representations for a linking-based image segmentation model","authors":"W. Niessen, K. Vincken, M. Viergever","doi":"10.1109/MMBIA.1996.534078","DOIUrl":"https://doi.org/10.1109/MMBIA.1996.534078","url":null,"abstract":"Different multiscale generators are qualitatively compared with respect to their performance within a multiscale linking model for image segmentation. The linking model used is the hyperstack that was inspired by linear scale space theory. The authors discuss which properties of this paradigm are essential to determine which multiscale representations are suited as input to the hyperstack. If selected, one of the main problems the authors tackle is the estimation of the local scale such that the various stacks of images can effectively be compared. For nonlinear multiscale representations, which cart be written as modified diffusion equations, an upper bound can be achieved by synchronizing the evolution parameter. The synchronization is empirically verified by counting the number of elliptic patches at corresponding scales. The authors compare the resulting stacks of images and the segmentation on a test image and a coronal MR brain image.","PeriodicalId":436387,"journal":{"name":"Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis","volume":"275 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114566346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1996-06-21DOI: 10.1109/MMBIA.1996.534081
K. Deguchi, Takayuki Okatani
Describes an approach to reconstructing a shape from it's shaded image in the case where a point light source is at the projection center. This condition well approximates the imaging system of an endoscope. In this case, the image gray level depends on not only the gradient of the object surface but also the distance from the light source to each point on the surface. To deal with this difficulty, the authors introduce the evolution equation for equal-range contours on the surface. Propagating this contour by solving the equation, one can reconstruct a shape. Experimental results far real medical endoscope images of a human stomach inner wall show feasibility of this method, and present a promising technique for morphological analysis of tumors on human inner organs.
{"title":"Shape reconstruction from an endoscope image by shape-from-shading technique for a point light source at the projection center","authors":"K. Deguchi, Takayuki Okatani","doi":"10.1109/MMBIA.1996.534081","DOIUrl":"https://doi.org/10.1109/MMBIA.1996.534081","url":null,"abstract":"Describes an approach to reconstructing a shape from it's shaded image in the case where a point light source is at the projection center. This condition well approximates the imaging system of an endoscope. In this case, the image gray level depends on not only the gradient of the object surface but also the distance from the light source to each point on the surface. To deal with this difficulty, the authors introduce the evolution equation for equal-range contours on the surface. Propagating this contour by solving the equation, one can reconstruct a shape. Experimental results far real medical endoscope images of a human stomach inner wall show feasibility of this method, and present a promising technique for morphological analysis of tumors on human inner organs.","PeriodicalId":436387,"journal":{"name":"Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125792998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1996-06-21DOI: 10.1109/MMBIA.1996.534053
F. Maes, A. Collignon, D. Vandermeulen, G. Marchal, P. Suetens
Mutual information of image intensities has been proposed as a new matching criterion for automated multi-modality image registration. In this paper the authors give experimental evidence of the power and the generality of the mutual information criterion by showing results for various applications involving CT, MR and PET images. The authors' results illustrate the large applicability of the approach and demonstrate its high suitability for routine use in clinical practice.
{"title":"Multi-modality image registration by maximization of mutual information","authors":"F. Maes, A. Collignon, D. Vandermeulen, G. Marchal, P. Suetens","doi":"10.1109/MMBIA.1996.534053","DOIUrl":"https://doi.org/10.1109/MMBIA.1996.534053","url":null,"abstract":"Mutual information of image intensities has been proposed as a new matching criterion for automated multi-modality image registration. In this paper the authors give experimental evidence of the power and the generality of the mutual information criterion by showing results for various applications involving CT, MR and PET images. The authors' results illustrate the large applicability of the approach and demonstrate its high suitability for routine use in clinical practice.","PeriodicalId":436387,"journal":{"name":"Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130884878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1996-06-21DOI: 10.1109/MMBIA.1996.534067
M. Vaillant, C. Davatzikos, R. Bryan
Parametric representations of anatomical structures provide useful mathematical descriptions for many medical imaging applications, including morphological analysis of the brain. Here, the authors develop a methodology for obtaining a parametric representation of the deep cortical folds of the brain utilizing characteristics of the cortical shape. They first find a mathematical representation of the outer cortical surface using a deformable surface algorithm. Using the principal curvatures of the resulting surface, the authors then identify the edges on the sulci on it, and they initialize active contours along them. An external force field guides an active contour to the deep edge of a sulcus, along the medial surface of a cortical fold. A parametric description of a sulcal surface is obtained as the active contour traverses the sulcus, sweeping a surface resembling a convoluted ribbon embedded in 3D. Here, the authors present results using magnetic resonance images.
{"title":"Finding 3D parametric representations of the deep cortical folds","authors":"M. Vaillant, C. Davatzikos, R. Bryan","doi":"10.1109/MMBIA.1996.534067","DOIUrl":"https://doi.org/10.1109/MMBIA.1996.534067","url":null,"abstract":"Parametric representations of anatomical structures provide useful mathematical descriptions for many medical imaging applications, including morphological analysis of the brain. Here, the authors develop a methodology for obtaining a parametric representation of the deep cortical folds of the brain utilizing characteristics of the cortical shape. They first find a mathematical representation of the outer cortical surface using a deformable surface algorithm. Using the principal curvatures of the resulting surface, the authors then identify the edges on the sulci on it, and they initialize active contours along them. An external force field guides an active contour to the deep edge of a sulcus, along the medial surface of a cortical fold. A parametric description of a sulcal surface is obtained as the active contour traverses the sulcus, sweeping a surface resembling a convoluted ribbon embedded in 3D. Here, the authors present results using magnetic resonance images.","PeriodicalId":436387,"journal":{"name":"Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126340920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1996-06-21DOI: 10.1109/MMBIA.1996.534080
F. Bookstein
Procrustes superposition and the thin-plate spline each principally developed within the context of discrete landmark data, can be combined in a novel adaptive filter for detecting localized group differences of outline shape.
{"title":"Landmark methods for forms without landmarks: localizing group differences in outline shape","authors":"F. Bookstein","doi":"10.1109/MMBIA.1996.534080","DOIUrl":"https://doi.org/10.1109/MMBIA.1996.534080","url":null,"abstract":"Procrustes superposition and the thin-plate spline each principally developed within the context of discrete landmark data, can be combined in a novel adaptive filter for detecting localized group differences of outline shape.","PeriodicalId":436387,"journal":{"name":"Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128039383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1996-06-21DOI: 10.1109/MMBIA.1996.534072
A. Goshtasby, D. Turner
A method is introduced for fusing the short-axis and long-axis cardiac MR images into an isotropic volume image. A volume image obtained by this method contains the left ventricular (LV) cavity in one piece, facilitating measurement of its shape and volume. The main goal in this image fusion is to reconstruct the LV cavity in volume form and in high resolution. The accuracy of the method is measured using a synthetic image. Examples of image fusion using real images are also presented.
{"title":"Fusion of short-axis and long-axis cardiac MR images","authors":"A. Goshtasby, D. Turner","doi":"10.1109/MMBIA.1996.534072","DOIUrl":"https://doi.org/10.1109/MMBIA.1996.534072","url":null,"abstract":"A method is introduced for fusing the short-axis and long-axis cardiac MR images into an isotropic volume image. A volume image obtained by this method contains the left ventricular (LV) cavity in one piece, facilitating measurement of its shape and volume. The main goal in this image fusion is to reconstruct the LV cavity in volume form and in high resolution. The accuracy of the method is measured using a synthetic image. Examples of image fusion using real images are also presented.","PeriodicalId":436387,"journal":{"name":"Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115989177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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