In this paper an algorithm for accurate delineation of object boundaries is proposed. The method employs a superpixel algorithm to obtain an oversegmentation of the input image, used as a constraint in the task. A shape model is built by applying Principal Geodesic Analysis on angular representation of automatically placed uniformly distant landmark points. The shape model is used to detect the boundaries of an object on a given image by iterative elongation of a partial boundary along borders of superpixels. Contrary to many state-of-the-art methods, the proposed approach does not need an initial boundary. The algorithm was tested on two natural and two synthetic sets of images. Mean Dice coefficients between 0.91 and 0.97 were obtained. In almost all cases the object was found. In areas of relatively high gradient magnitude the borders are delineated very accurately, though further research is needed to improve the accuracy in areas of low gradient magnitude and automatically select the parameters of the proposed error function.
{"title":"PRINCIPAL GEODESIC ANALYSIS BOUNDARY DELINEATION WITH SUPERPIXEL-BASED CONSTRAINTS","authors":"Mateusz Baran, Z. Tabor","doi":"10.5566/IAS.1712","DOIUrl":"https://doi.org/10.5566/IAS.1712","url":null,"abstract":"In this paper an algorithm for accurate delineation of object boundaries is proposed. The method employs a superpixel algorithm to obtain an oversegmentation of the input image, used as a constraint in the task. A shape model is built by applying Principal Geodesic Analysis on angular representation of automatically placed uniformly distant landmark points. The shape model is used to detect the boundaries of an object on a given image by iterative elongation of a partial boundary along borders of superpixels. Contrary to many state-of-the-art methods, the proposed approach does not need an initial boundary. The algorithm was tested on two natural and two synthetic sets of images. Mean Dice coefficients between 0.91 and 0.97 were obtained. In almost all cases the object was found. In areas of relatively high gradient magnitude the borders are delineated very accurately, though further research is needed to improve the accuracy in areas of low gradient magnitude and automatically select the parameters of the proposed error function.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"1 1","pages":"223-232"},"PeriodicalIF":0.9,"publicationDate":"2017-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82380693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Kubínová, B. Radochová, Z. Lhotáková, Zuzana Kubínová, J. Albrechtová
This review presents an historical overview of stereological methods used for the quantitative evaluation of plant anatomical and cytological structures. It includes the origins of these methods up to the most recent developments such as the application of stereology based on 3D images. We focus especially on leaf, as the vast majority of studies of plant microscopic structure examine this organ. An overview of plant cell ultrastructure measurements as well as plant anatomical characteristics (e.g. plant tissue volume density, internal leaf surface area, number and mean size of mesophyll cells and chloroplast number), which were estimated by stereological methods most frequently, is presented. We emphasize the importance of proper sampling needed for unbiased measurements. Furthermore, we mention other methods used for plant morphometric studies and briefly discuss their relevance, precision, unbiasedness and efficiency in comparison with unbiased stereology. Finally, we discuss reasons for the sparse use of stereology in plant anatomy and consider the future of stereology in plant research.
{"title":"STEREOLOGY, AN UNBIASED METHODOLOGICAL APPROACH TO STUDY PLANT ANATOMY AND CYTOLOGY: PAST, PRESENT AND FUTURE","authors":"L. Kubínová, B. Radochová, Z. Lhotáková, Zuzana Kubínová, J. Albrechtová","doi":"10.5566/IAS.1848","DOIUrl":"https://doi.org/10.5566/IAS.1848","url":null,"abstract":"This review presents an historical overview of stereological methods used for the quantitative evaluation of plant anatomical and cytological structures. It includes the origins of these methods up to the most recent developments such as the application of stereology based on 3D images. We focus especially on leaf, as the vast majority of studies of plant microscopic structure examine this organ. An overview of plant cell ultrastructure measurements as well as plant anatomical characteristics (e.g. plant tissue volume density, internal leaf surface area, number and mean size of mesophyll cells and chloroplast number), which were estimated by stereological methods most frequently, is presented. We emphasize the importance of proper sampling needed for unbiased measurements. Furthermore, we mention other methods used for plant morphometric studies and briefly discuss their relevance, precision, unbiasedness and efficiency in comparison with unbiased stereology. Finally, we discuss reasons for the sparse use of stereology in plant anatomy and consider the future of stereology in plant research.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"27 1","pages":"187-205"},"PeriodicalIF":0.9,"publicationDate":"2017-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77954078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose an invariant three-point curvature approximation for plane curves based on the arc of a parabolic sector, and we analyze how closely this approximation is to the true curvature of the curve. We compare our results with the obtained with other invariant three-point curvature approximations. Finally, an application is discussed.
{"title":"CURVATURE APPROXIMATION FROM PARABOLIC SECTORS","authors":"X. Gual-Arnau, M. V. I. Gual, J. Monterde","doi":"10.5566/ias.1702","DOIUrl":"https://doi.org/10.5566/ias.1702","url":null,"abstract":"We propose an invariant three-point curvature approximation for plane curves based on the arc of a parabolic sector, and we analyze how closely this approximation is to the true curvature of the curve. We compare our results with the obtained with other invariant three-point curvature approximations. Finally, an application is discussed.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"12 1","pages":"233-241"},"PeriodicalIF":0.9,"publicationDate":"2017-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84629699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A number of bidimensional random structures with increasing densities are simulated to explore possible links between Euler-Poincare characteristic (EPC), or connectivity, and percolation threshold. For each structure model, the percolation threshold is compared with a number of typical points (extrema, zero crossings...) of the EPC curve. From these exercises, it can be concluded that the percolation threshold cannot be generally predicted using the evolution of the EPC.
{"title":"PERCOLATION TRANSITION AND TOPOLOGY","authors":"P. Jouannot-Chesney, J. Jernot, C. Lantuéjoul","doi":"10.5566/IAS.1573","DOIUrl":"https://doi.org/10.5566/IAS.1573","url":null,"abstract":"A number of bidimensional random structures with increasing densities are simulated to explore possible links between Euler-Poincare characteristic (EPC), or connectivity, and percolation threshold. For each structure model, the percolation threshold is compared with a number of typical points (extrema, zero crossings...) of the EPC curve. From these exercises, it can be concluded that the percolation threshold cannot be generally predicted using the evolution of the EPC.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"91 1","pages":"95-103"},"PeriodicalIF":0.9,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79020237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elaheh Aghabalaei Khordehchi, A. Ayatollahi, M. Daliri
Lung cancer is one of the most common diseases in the world that can be treated if the lung nodules are detected in their early stages of growth. This study develops a new framework for computer-aided detection of pulmonary nodules thorough a fully-automatic analysis of Computed Tomography (CT) images. In the present work, the multi-layer CT data is fed into a pre-processing step that exploits an adaptive diffusion-based smoothing algorithm in which the parameters are automatically tuned using an adaptation technique. After multiple levels of morphological filtering, the Regions of Interest (ROIs) are extracted from the smoothed images. The Statistical Region Merging (SRM) algorithm is applied to the ROIs in order to segment each layer of the CT data. Extracted segments in consecutive layers are then analyzed in such a way that if they intersect at more than a predefined number of pixels, they are labeled with a similar index. The boundaries of the segments in adjacent layers which have the same indices are then connected together to form three-dimensional objects as the nodule candidates. After extracting four spectral, one morphological, and one textural feature from all candidates, they are finally classified into nodules and non-nodules using the Support Vector Machine (SVM) classifier. The proposed framework has been applied to two sets of lung CT images and its performance has been compared to that of nine other competing state-of-the-art methods. The considerable efficiency of the proposed approach has been proved quantitatively and validated by clinical experts as well.
{"title":"AUTOMATIC LUNG NODULE DETECTION BASED ON STATISTICAL REGION MERGING AND SUPPORT VECTOR MACHINES","authors":"Elaheh Aghabalaei Khordehchi, A. Ayatollahi, M. Daliri","doi":"10.5566/IAS.1679","DOIUrl":"https://doi.org/10.5566/IAS.1679","url":null,"abstract":"Lung cancer is one of the most common diseases in the world that can be treated if the lung nodules are detected in their early stages of growth. This study develops a new framework for computer-aided detection of pulmonary nodules thorough a fully-automatic analysis of Computed Tomography (CT) images. In the present work, the multi-layer CT data is fed into a pre-processing step that exploits an adaptive diffusion-based smoothing algorithm in which the parameters are automatically tuned using an adaptation technique. After multiple levels of morphological filtering, the Regions of Interest (ROIs) are extracted from the smoothed images. The Statistical Region Merging (SRM) algorithm is applied to the ROIs in order to segment each layer of the CT data. Extracted segments in consecutive layers are then analyzed in such a way that if they intersect at more than a predefined number of pixels, they are labeled with a similar index. The boundaries of the segments in adjacent layers which have the same indices are then connected together to form three-dimensional objects as the nodule candidates. After extracting four spectral, one morphological, and one textural feature from all candidates, they are finally classified into nodules and non-nodules using the Support Vector Machine (SVM) classifier. The proposed framework has been applied to two sets of lung CT images and its performance has been compared to that of nine other competing state-of-the-art methods. The considerable efficiency of the proposed approach has been proved quantitatively and validated by clinical experts as well.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"26 1","pages":"65-78"},"PeriodicalIF":0.9,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78227336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advanced driver assistance systems (ADAS) have been developed to automate and modify vehicles for safety and better driving experience. Among all computer vision modules in ADAS, 360-degree surround view generation of immediate surroundings of the vehicle is very important, due to application in on-road traffic assistance, parking assistance etc. This paper presents a novel algorithm for fast and computationally efficient transformation of input fisheye images into required top down view. This paper also presents a generalized framework for generating top down view of images captured by cameras with fish-eye lenses mounted on vehicles, irrespective of pitch or tilt angle. The proposed approach comprises of two major steps, viz. correcting the fish-eye lens images to rectilinear images, and generating top-view perspective of the corrected images. The images captured by the fish-eye lens possess barrel distortion, for which a nonlinear and non-iterative method is used. Thereafter, homography is used to obtain top-down view of corrected images. This paper also targets to develop surroundings of the vehicle for wider distortion less field of view and camera perspective independent top down view, with minimum computation cost which is essential due to limited computation power on vehicles.
{"title":"A GENERALIZED NON-LINEAR METHOD FOR DISTORTION CORRECTION AND TOP-DOWN VIEW CONVERSION OF FISH EYE IMAGES","authors":"V. Bawa, Krishan Kumar, Vinay Kumar","doi":"10.5566/IAS.1660","DOIUrl":"https://doi.org/10.5566/IAS.1660","url":null,"abstract":"Advanced driver assistance systems (ADAS) have been developed to automate and modify vehicles for safety and better driving experience. Among all computer vision modules in ADAS, 360-degree surround view generation of immediate surroundings of the vehicle is very important, due to application in on-road traffic assistance, parking assistance etc. This paper presents a novel algorithm for fast and computationally efficient transformation of input fisheye images into required top down view. This paper also presents a generalized framework for generating top down view of images captured by cameras with fish-eye lenses mounted on vehicles, irrespective of pitch or tilt angle. The proposed approach comprises of two major steps, viz. correcting the fish-eye lens images to rectilinear images, and generating top-view perspective of the corrected images. The images captured by the fish-eye lens possess barrel distortion, for which a nonlinear and non-iterative method is used. Thereafter, homography is used to obtain top-down view of corrected images. This paper also targets to develop surroundings of the vehicle for wider distortion less field of view and camera perspective independent top down view, with minimum computation cost which is essential due to limited computation power on vehicles.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"26 1","pages":"141-150"},"PeriodicalIF":0.9,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85357386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Cavalieri method allows to estimate the volume of a compact object from area measurements in equidistant parallel planar sections. However, the spacing and thickness of sections can be quite irregular in applications. Recent publications have thus focused on the effect of random variability in section spacing, showing that the classical Cavalieri estimator is still unbiased when the stack of parallel planes is stationary, but that the existing variance approximations must be adjusted. The present paper considers the special situation, where the distances between consecutive section planes can be measured and thus where Cavalieri’s estimator can be replaced by a quadrature rule with randomized sampling points. We show that, under mild conditions, the trapezoid rule and Simpson’s rule lead to unbiased volume estimators and give simulation results that indicate that a considerable variance reduction compared to the generalized Cavalieri estimator can be achieved.
{"title":"THE CAVALIERI ESTIMATOR WITH UNEQUAL SECTION SPACING REVISITED","authors":"M. Kiderlen, K. Dorph‐Petersen","doi":"10.5566/IAS.1723","DOIUrl":"https://doi.org/10.5566/IAS.1723","url":null,"abstract":"The Cavalieri method allows to estimate the volume of a compact object from area measurements in equidistant parallel planar sections. However, the spacing and thickness of sections can be quite irregular in applications. Recent publications have thus focused on the effect of random variability in section spacing, showing that the classical Cavalieri estimator is still unbiased when the stack of parallel planes is stationary, but that the existing variance approximations must be adjusted. The present paper considers the special situation, where the distances between consecutive section planes can be measured and thus where Cavalieri’s estimator can be replaced by a quadrature rule with randomized sampling points. We show that, under mild conditions, the trapezoid rule and Simpson’s rule lead to unbiased volume estimators and give simulation results that indicate that a considerable variance reduction compared to the generalized Cavalieri estimator can be achieved.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"24 1","pages":"133-139"},"PeriodicalIF":0.9,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81627339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The nucleator is a design unbiased method of local stereology for estimating the volume of a bounded object. The only information required lies in the intersection of the object with an isotropic random ray emanating from a fixed point (called the pivotal point) associated with the object. For instance, the volume of a neuron can be estimated from a random ray emanating from its nucleolus. The nucleator is extensively used in biosciences because it is efficient and easy to apply. The estimator variance can be reduced by increasing the number of rays. In an earlier paper a systematic sampling design was proposed, and theoretical variance predictors were derived, for the corresponding volume estimator. Being the only variance predictors hitherto available for the nucleator, our basic goal was to check their statistical performance by means of Monte Carlo resampling on computer reconstructions of real objects. As a plus, the empirical distribution of the volume estimator revealed statistical properties of practical relevance.
{"title":"ON THE PRECISION OF THE NUCLEATOR","authors":"Javier González-Villa, M. Cruz, L. Cruz-Orive","doi":"10.5566/IAS.1671","DOIUrl":"https://doi.org/10.5566/IAS.1671","url":null,"abstract":"The nucleator is a design unbiased method of local stereology for estimating the volume of a bounded object. The only information required lies in the intersection of the object with an isotropic random ray emanating from a fixed point (called the pivotal point) associated with the object. For instance, the volume of a neuron can be estimated from a random ray emanating from its nucleolus. The nucleator is extensively used in biosciences because it is efficient and easy to apply. The estimator variance can be reduced by increasing the number of rays. In an earlier paper a systematic sampling design was proposed, and theoretical variance predictors were derived, for the corresponding volume estimator. Being the only variance predictors hitherto available for the nucleator, our basic goal was to check their statistical performance by means of Monte Carlo resampling on computer reconstructions of real objects. As a plus, the empirical distribution of the volume estimator revealed statistical properties of practical relevance.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"6 1","pages":"121-132"},"PeriodicalIF":0.9,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89271181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Comparison of the quality of despeckled US medical images is complicated because there is no image of a human body that would be free of speckles and could serve as a reference. A number of various image metrics are currently used for comparison of filtering methods; however, they do not satisfactorily represent the visual quality of images and medical expert’s satisfaction with images. This paper proposes an innovative use of relative multivariate kurtosis for the evaluation of the most important edges in an image. Multivariate kurtosis allows one to introduce an order among the filtered images and can be used as one of the metrics for image quality evaluation. At present there is no method which would jointly consider individual metrics. Furthermore, these metrics are typically defined by comparing the noisy original and filtered images, which is incorrect since the noisy original cannot serve as a golden standard. In contrast to this, the proposed kurtosis is the absolute measure, which is calculated independently of any reference image and it agrees with the medical expert’s satisfaction to a large extent. The paper presents a numerical procedure for calculating kurtosis and describes results of such calculations for a computer-generated noisy image, images of a general purpose phantom and a cyst phantom, as well as real-life images of thyroid and carotid artery obtained with SonixTouch ultrasound machine. 16 different methods of image despeckling are compared via kurtosis. The paper shows that visually more satisfactory despeckling results are associated with higher kurtosis, and to a certain degree kurtosis can be used as a single metric for evaluation of image quality.
{"title":"COMPARISON OF ULTRASOUND IMAGE FILTERING METHODS BY MEANS OF MULTIVARIABLE KURTOSIS","authors":"Mariusz Nieniewski, Pawel Zajaczkowski","doi":"10.5566/IAS.1639","DOIUrl":"https://doi.org/10.5566/IAS.1639","url":null,"abstract":"Comparison of the quality of despeckled US medical images is complicated because there is no image of a human body that would be free of speckles and could serve as a reference. A number of various image metrics are currently used for comparison of filtering methods; however, they do not satisfactorily represent the visual quality of images and medical expert’s satisfaction with images. This paper proposes an innovative use of relative multivariate kurtosis for the evaluation of the most important edges in an image. Multivariate kurtosis allows one to introduce an order among the filtered images and can be used as one of the metrics for image quality evaluation. At present there is no method which would jointly consider individual metrics. Furthermore, these metrics are typically defined by comparing the noisy original and filtered images, which is incorrect since the noisy original cannot serve as a golden standard. In contrast to this, the proposed kurtosis is the absolute measure, which is calculated independently of any reference image and it agrees with the medical expert’s satisfaction to a large extent. The paper presents a numerical procedure for calculating kurtosis and describes results of such calculations for a computer-generated noisy image, images of a general purpose phantom and a cyst phantom, as well as real-life images of thyroid and carotid artery obtained with SonixTouch ultrasound machine. 16 different methods of image despeckling are compared via kurtosis. The paper shows that visually more satisfactory despeckling results are associated with higher kurtosis, and to a certain degree kurtosis can be used as a single metric for evaluation of image quality.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"29 1","pages":"79-94"},"PeriodicalIF":0.9,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80510554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Studies have provided qualitative evidence of de-myelination and re-myelination in aged brain white matter. However, there have been no quantitative evidences of degeneration and regeneration of myelin sheaths in white matter. The present study was designed to investigate the quantitative changes in myelin sheaths using unbiased stereological techniques and qualitative changes using electron microscopy in aged brain white matter. Results obtained showed that in brain white matter, the total volume of myelin sheaths of old-age female rats was not significantly different from that of young female rats, but the total length of myelinated fibers in old female rats was significantly decreased by 46.1% when compared with that of young female rats. Myelin sheath volume per unit length of myelinated fibers of old female rats was significantly increased by 43.4% compared with that of young female rats. The mean thickness of myelin sheaths in the white matter of the old rats was significantly increased by 33.3%, when compared with that of young female rats. In age-related loss of myelinated fibers, most fibers had diameters less than 1.4 μm, and myelin sheath thicknesses less than 0.14 μm, but the length of myelinated fibers with diameters more than 0.6 μm and myelin sheath thicknesses more than 0.22 μm increased with age. Myelinated fibers with ratios of myelin sheath thicknesses to myelinated fiber external diameter less than 0.21 were significantly lower in elderly rats than in young rats. However, the total length of myelinated fibers with ratios of myelin sheath thicknesses to myelinated fiber external diameter more than 0.23 was higher in aged rats than in young rats. About 6.58% of myelin sheaths showed degenerative alterations, while 0.88% myelin sheaths showed regenerative alterations. This study provides stereological evidence not only for degeneration but also regeneration of myelin sheaths in aged white matter.
{"title":"STEREOLOGICAL EVIDENCE FOR DE/RE-GENERATION OF MYELIN SHEATHS IN AGED BRAIN WHITE MATTER OF FEMALE RATS","authors":"Chen Li, Lei Zhang, Qiaoya Ma, Yong Tang, Ya He","doi":"10.5566/IAS.1436","DOIUrl":"https://doi.org/10.5566/IAS.1436","url":null,"abstract":"Studies have provided qualitative evidence of de-myelination and re-myelination in aged brain white matter. However, there have been no quantitative evidences of degeneration and regeneration of myelin sheaths in white matter. The present study was designed to investigate the quantitative changes in myelin sheaths using unbiased stereological techniques and qualitative changes using electron microscopy in aged brain white matter. Results obtained showed that in brain white matter, the total volume of myelin sheaths of old-age female rats was not significantly different from that of young female rats, but the total length of myelinated fibers in old female rats was significantly decreased by 46.1% when compared with that of young female rats. Myelin sheath volume per unit length of myelinated fibers of old female rats was significantly increased by 43.4% compared with that of young female rats. The mean thickness of myelin sheaths in the white matter of the old rats was significantly increased by 33.3%, when compared with that of young female rats. In age-related loss of myelinated fibers, most fibers had diameters less than 1.4 μm, and myelin sheath thicknesses less than 0.14 μm, but the length of myelinated fibers with diameters more than 0.6 μm and myelin sheath thicknesses more than 0.22 μm increased with age. Myelinated fibers with ratios of myelin sheath thicknesses to myelinated fiber external diameter less than 0.21 were significantly lower in elderly rats than in young rats. However, the total length of myelinated fibers with ratios of myelin sheath thicknesses to myelinated fiber external diameter more than 0.23 was higher in aged rats than in young rats. About 6.58% of myelin sheaths showed degenerative alterations, while 0.88% myelin sheaths showed regenerative alterations. This study provides stereological evidence not only for degeneration but also regeneration of myelin sheaths in aged white matter.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"10 1","pages":"111-120"},"PeriodicalIF":0.9,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89785479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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