This study was carefully designed to determine the section compression of paraffin embedded sections. Two sections (one with thickness 5 µm and one 10 µm set by microtome) were cut from each of 2 sets of 12 testicular tissue (adult rats) blocks and stained with hematoxylin. Using scanned images, the area and the vertical (along the sectioning direction) and horizontal diameters of the block face were measured and compared with those of the unstained, stained or coverslipped section. Using the coverslipped section, the vertical and horizontal diameters of round spermatid nuclear profiles and the actual thickness of section were measured with light microscopy. Overall, the area of the coverslipped section was reduced by 5.5%-8.6% (on average) in comparison with that of the block face, with 69.5%-84.4% of the reduction being contributed by section compression in the process of section cutting, mounting and drying. The vertical (linear) compression of section, the primary cause of section area compression, was 5.9%-8.9%. The vertical compression of nuclear profiles was 1.5%-2.3% in 2 sets of sections and 5.2%-5.7% in other sections, indicating a non-uniform compression of structures within some sections depending on procedures of section drying. The measured mean thickness of sections decreased by 3.1%-5.0%.
{"title":"A STUDY OF AREA AND THICKNESS COMPRESSION OF PARAFFIN SECTIONS","authors":"Y. Xiang, Yang Guo, Zheng-Wei Yang","doi":"10.5566/IAS.1868","DOIUrl":"https://doi.org/10.5566/IAS.1868","url":null,"abstract":"This study was carefully designed to determine the section compression of paraffin embedded sections. Two sections (one with thickness 5 µm and one 10 µm set by microtome) were cut from each of 2 sets of 12 testicular tissue (adult rats) blocks and stained with hematoxylin. Using scanned images, the area and the vertical (along the sectioning direction) and horizontal diameters of the block face were measured and compared with those of the unstained, stained or coverslipped section. Using the coverslipped section, the vertical and horizontal diameters of round spermatid nuclear profiles and the actual thickness of section were measured with light microscopy. Overall, the area of the coverslipped section was reduced by 5.5%-8.6% (on average) in comparison with that of the block face, with 69.5%-84.4% of the reduction being contributed by section compression in the process of section cutting, mounting and drying. The vertical (linear) compression of section, the primary cause of section area compression, was 5.9%-8.9%. The vertical compression of nuclear profiles was 1.5%-2.3% in 2 sets of sections and 5.2%-5.7% in other sections, indicating a non-uniform compression of structures within some sections depending on procedures of section drying. The measured mean thickness of sections decreased by 3.1%-5.0%.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"5 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2018-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90157728","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}
Markus Kronenberger, K. Schladitz, B. Hamann, H. Hagen
This paper tackles the non-trivial image-processing task to segment hook-ended fibers in three-dimensional images. For this purpose, a novel segmentation method is presented that relies on the following observation: For a single fiber the configurations of principal curvatures that can occur on its surface are limited. Deviations from these configurations indicate potential overlaps of fibers. The method that was developed based on this observation is used to separate several simulated clusters of touching fibers as a proof-of-concept. Further, it is applied to two images of cracked steel fiber reinforced concrete specimens arising from a 4-point bending test. The method's performance is compared to manual separation. Overall, we can state that the proposed method yields satisfying results when data meets the following criteria: Low fiber volume density, circular fiber cross section and sufficient spatial resolution of fiber-fiber contacts.
{"title":"FIBER SEGMENTATION IN CRACK REGIONS OF STEEL FIBER REINFORCED CONCRETE USING PRINCIPAL CURVATURE","authors":"Markus Kronenberger, K. Schladitz, B. Hamann, H. Hagen","doi":"10.5566/IAS.1914","DOIUrl":"https://doi.org/10.5566/IAS.1914","url":null,"abstract":"This paper tackles the non-trivial image-processing task to segment hook-ended fibers in three-dimensional images. For this purpose, a novel segmentation method is presented that relies on the following observation: For a single fiber the configurations of principal curvatures that can occur on its surface are limited. Deviations from these configurations indicate potential overlaps of fibers. The method that was developed based on this observation is used to separate several simulated clusters of touching fibers as a proof-of-concept. Further, it is applied to two images of cracked steel fiber reinforced concrete specimens arising from a 4-point bending test. The method's performance is compared to manual separation. Overall, we can state that the proposed method yields satisfying results when data meets the following criteria: Low fiber volume density, circular fiber cross section and sufficient spatial resolution of fiber-fiber contacts.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"60 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2018-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89356775","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}
Over the years image quality assessment is one of the active area of research in image processing. Distortion in images can be caused by various sources like noise, blur, transmission channel errors, compression artifacts etc. Image distortions can occur during the image acquisition process (blur/noise), image compression (ringing and blocking artifacts) or during the transmission process. A single image can be distorted by multiple sources and assessing quality of such images is an extremely challenging task. The human visual system can easily identify image quality in such cases, but for a computer algorithm performing the task of quality assessment is a very difficult. In this paper, we propose a new no-reference image quality assessment for images corrupted by more than one type of distortions. The proposed technique is compared with the best-known framework for image quality assessment for multiply distorted images and standard state of the art Full reference and No-reference image quality assessment techniques available.
{"title":"NO-REFERENCE IMAGE QUALITY MEASURE FOR IMAGES WITH MULTIPLE DISTORTIONS USING RANDOM FORESTS FOR MULTI METHOD FUSION","authors":"K. De, Masilamani","doi":"10.5566/IAS.1534","DOIUrl":"https://doi.org/10.5566/IAS.1534","url":null,"abstract":"Over the years image quality assessment is one of the active area of research in image processing. Distortion in images can be caused by various sources like noise, blur, transmission channel errors, compression artifacts etc. Image distortions can occur during the image acquisition process (blur/noise), image compression (ringing and blocking artifacts) or during the transmission process. A single image can be distorted by multiple sources and assessing quality of such images is an extremely challenging task. The human visual system can easily identify image quality in such cases, but for a computer algorithm performing the task of quality assessment is a very difficult. In this paper, we propose a new no-reference image quality assessment for images corrupted by more than one type of distortions. The proposed technique is compared with the best-known framework for image quality assessment for multiply distorted images and standard state of the art Full reference and No-reference image quality assessment techniques available. ","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"15 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2018-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74538499","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}
Vincent Bortolussi, B. Figliuzzi, F. Willot, M. Faessel, M. Jeandin
In this article, we study the microstructure of cold sprayed films of copper particles deposited onto a carbon fiber reinforced polymer. The microstructure of the coating is made of a packing of seemingly round-shaped particles of varying sizes embedded in a polymer matrix. The copper particles are separated by thin interstices. The coating is designed to cover the body of recent commercial aircrafts. Its role is to protect the aircraft from lightning impact by ensuring that the surface is conductive enough to evacuate electrical charges. A high resistivity contrast is observed between the copper particles and the polymer matrix. Therefore, the global resistivity of the material is highly dependent on the microstructure geometry.Following an approach commonly used in materials science, to investigate its influence on the electrical properties of the global material at the macroscopic scale, we design a 3D multiscale stochastic model that enables us to simulate the microstructure. The model is based upon a generalization of the classical JohnsonMehl tessellation, which accounts for the interstices that appear between copper particles. The method is very general and could potentially be applied to model any microstructure exhibiting similar interstices between aggregates of particles.
{"title":"MORPHOLOGICAL MODELING OF COLD SPRAY COATINGS","authors":"Vincent Bortolussi, B. Figliuzzi, F. Willot, M. Faessel, M. Jeandin","doi":"10.5566/IAS.1894","DOIUrl":"https://doi.org/10.5566/IAS.1894","url":null,"abstract":"In this article, we study the microstructure of cold sprayed films of copper particles deposited onto a carbon fiber reinforced polymer. The microstructure of the coating is made of a packing of seemingly round-shaped particles of varying sizes embedded in a polymer matrix. The copper particles are separated by thin interstices. The coating is designed to cover the body of recent commercial aircrafts. Its role is to protect the aircraft from lightning impact by ensuring that the surface is conductive enough to evacuate electrical charges. A high resistivity contrast is observed between the copper particles and the polymer matrix. Therefore, the global resistivity of the material is highly dependent on the microstructure geometry.Following an approach commonly used in materials science, to investigate its influence on the electrical properties of the global material at the macroscopic scale, we design a 3D multiscale stochastic model that enables us to simulate the microstructure. The model is based upon a generalization of the classical JohnsonMehl tessellation, which accounts for the interstices that appear between copper particles. The method is very general and could potentially be applied to model any microstructure exhibiting similar interstices between aggregates of particles.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"3 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2018-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84209808","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}
Scientific work is often very time consuming and the results are frequently not clear for the audience. A sense of humour is a good tool for demonstration of complicated problems. The paper describes selected cases from the past 30 years in which a sense of humour together with appropriate cartoons were successfully applied.
{"title":"SOLVING PROBLEMS IN STEREOLOGY WITHOUT MATHEMATICAL FORMALISM","authors":"L. Wojnar","doi":"10.5566/IAS.1922","DOIUrl":"https://doi.org/10.5566/IAS.1922","url":null,"abstract":"Scientific work is often very time consuming and the results are frequently not clear for the audience. A sense of humour is a good tool for demonstration of complicated problems. The paper describes selected cases from the past 30 years in which a sense of humour together with appropriate cartoons were successfully applied. ","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"31 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2018-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79199062","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}
Lip-reading is typically known as visually interpreting the speaker's lip movements during speaking. Experiments over many years have revealed that speech intelligibility increases if visual facial information becomes available. This effect becomes more apparent in noisy environments. Taking steps toward automating this process, some challenges will be raised such as coarticulation phenomenon, visual units' type, features diversity and their inter-speaker dependency. While efforts have been made to overcome these challenges, presentation of a flawless lip-reading system is still under the investigations. This paper searches for a lipreading model with an efficiently developed incorporation and arrangement of processing blocks to extract highly discriminative visual features. Here, application of a properly structured Deep Belief Network (DBN)- based recognizer is highlighted. Multi-speaker (MS) and speaker-independent (SI) tasks are performed over CUAVE database, and phone recognition rates (PRRs) of 77.65% and 73.40% are achieved, respectively. The best word recognition rates (WRRs) achieved in the tasks of MS and SI are 80.25% and 76.91%, respectively. Resulted accuracies demonstrate that the proposed method outperforms the conventional Hidden Markov Model (HMM) and competes well with the state-of-the-art visual speech recognition works.
{"title":"LIP-READING VIA DEEP NEURAL NETWORKS USING HYBRID VISUAL FEATURES","authors":"Fatemeh Vakhshiteh, F. Almasganj, A. Nickabadi","doi":"10.5566/IAS.1859","DOIUrl":"https://doi.org/10.5566/IAS.1859","url":null,"abstract":"Lip-reading is typically known as visually interpreting the speaker's lip movements during speaking. Experiments over many years have revealed that speech intelligibility increases if visual facial information becomes available. This effect becomes more apparent in noisy environments. Taking steps toward automating this process, some challenges will be raised such as coarticulation phenomenon, visual units' type, features diversity and their inter-speaker dependency. While efforts have been made to overcome these challenges, presentation of a flawless lip-reading system is still under the investigations. This paper searches for a lipreading model with an efficiently developed incorporation and arrangement of processing blocks to extract highly discriminative visual features. Here, application of a properly structured Deep Belief Network (DBN)- based recognizer is highlighted. Multi-speaker (MS) and speaker-independent (SI) tasks are performed over CUAVE database, and phone recognition rates (PRRs) of 77.65% and 73.40% are achieved, respectively. The best word recognition rates (WRRs) achieved in the tasks of MS and SI are 80.25% and 76.91%, respectively. Resulted accuracies demonstrate that the proposed method outperforms the conventional Hidden Markov Model (HMM) and competes well with the state-of-the-art visual speech recognition works.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"5 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2018-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89447621","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}
Measuring the growth of spherulites in semi-crystalline thermoplastics helps to control and optimize industrial manufacturing processes of these materials. The growth can be observed in cross polarized images, taken at several time steps. The diameters of the spherulites are however measured manually in each step. Here, two approaches for replacing this tedious and time consuming method by automatic image analytic measurements are introduced. The first approach segments spherulites by finding salient 5x5 pixel patches in each time frame. Combining the information from all time frames into a 3D image yields the spherulites by a maximal flow graph cut in 3D. The growth is then measured by homography measurement. The second approach is closer to the manual method. Based on the Hough transform, spherulites are identified by their circular outline. The growth is then measured by comparing the radia of the least moving circles. The pros and cons of these methods are discussed based on synthetic image data as well as by comparison with manually measured growth rates.
{"title":"IMAGE ANALYTICAL DETERMINATION OF THE SPHERULITE GROWTH IN POLYPROPYLENE COMPOSITES","authors":"A. Moghiseh, K. Schladitz, A. Schlarb, B. Suksut","doi":"10.5566/IAS.1895","DOIUrl":"https://doi.org/10.5566/IAS.1895","url":null,"abstract":"Measuring the growth of spherulites in semi-crystalline thermoplastics helps to control and optimize industrial manufacturing processes of these materials. The growth can be observed in cross polarized images, taken at several time steps. The diameters of the spherulites are however measured manually in each step. Here, two approaches for replacing this tedious and time consuming method by automatic image analytic measurements are introduced. The first approach segments spherulites by finding salient 5x5 pixel patches in each time frame. Combining the information from all time frames into a 3D image yields the spherulites by a maximal flow graph cut in 3D. The growth is then measured by homography measurement. The second approach is closer to the manual method. Based on the Hough transform, spherulites are identified by their circular outline. The growth is then measured by comparing the radia of the least moving circles. The pros and cons of these methods are discussed based on synthetic image data as well as by comparison with manually measured growth rates. ","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"17 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2018-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88536651","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}
Forests are the lungs of our planet. Conserving the plants may require the development of an automated system that will identify plants using leaf features such as shape, color, and texture. In this paper, a leaf shape descriptor based on sinuosity coefficients is proposed. The sinuosity coefficients are defined using the sinuosity measure, which is a measure expressing the degree of meandering of a curve. The initial empirical experiments performed on the LeafSnap dataset on the usage of four sinuosity coefficients to characterize the leaf images using the Radial Basis Function Neural Network (RBF) and Multilayer Perceptron (MLP) classifiers achieved accurate classification rates of 88% and 65%, respectively. The proposed feature extraction technique is further enhanced through the addition of leaf geometrical features, and the accurate classification rates of 93% and 82% were achieved using RBF and MLP, respectively. The overall results achieved showed that the proposed feature extraction technique based on the sinuosity coefficients of leaves, complemented with geometrical features improve the accuracy rate of plant classification using leaf recognition.
{"title":"PLANT SPECIE CLASSIFICATION USING SINUOSITY COEFFICIENTS OF LEAVES","authors":"J. R. Kala, Serestina Viriri","doi":"10.5566/IAS.1821","DOIUrl":"https://doi.org/10.5566/IAS.1821","url":null,"abstract":"Forests are the lungs of our planet. Conserving the plants may require the development of an automated system that will identify plants using leaf features such as shape, color, and texture. In this paper, a leaf shape descriptor based on sinuosity coefficients is proposed. The sinuosity coefficients are defined using the sinuosity measure, which is a measure expressing the degree of meandering of a curve. The initial empirical experiments performed on the LeafSnap dataset on the usage of four sinuosity coefficients to characterize the leaf images using the Radial Basis Function Neural Network (RBF) and Multilayer Perceptron (MLP) classifiers achieved accurate classification rates of 88% and 65%, respectively. The proposed feature extraction technique is further enhanced through the addition of leaf geometrical features, and the accurate classification rates of 93% and 82% were achieved using RBF and MLP, respectively. The overall results achieved showed that the proposed feature extraction technique based on the sinuosity coefficients of leaves, complemented with geometrical features improve the accuracy rate of plant classification using leaf recognition.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"41 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2018-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80893752","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}
Eduardo Sant'Ana da Silva, Anderson Santos, H. Pedrini
Surface approximation plays an important role in several application fields, such as computer-aided design, computer graphics, remote sensing, computer vision, robotics, architecture, and manufacturing. A common problem present in these areas is to develop efficient methods for generating, processing, analyzing, and visualizing large amount of 3D data. Triangular meshes constitute a flexible representation of sampled points that are not regularly distributed in space, such that the model can be adaptively adjusted to the data density. The choice of metrics for building the triangular meshes is crucial to produce high quality models. This paper proposes and evaluates different measures to incrementally refine a Delaunay triangular mesh for image surface approximation until either a certain accuracy is obtained or a maximum number of iterations is achieved. Experiments on several data sets are performed to compare the quality of the resulting meshes.
{"title":"METRICS FOR IMAGE SURFACE APPROXIMATION BASED ON TRIANGULAR MESHES","authors":"Eduardo Sant'Ana da Silva, Anderson Santos, H. Pedrini","doi":"10.5566/IAS.1591","DOIUrl":"https://doi.org/10.5566/IAS.1591","url":null,"abstract":"Surface approximation plays an important role in several application fields, such as computer-aided design, computer graphics, remote sensing, computer vision, robotics, architecture, and manufacturing. A common problem present in these areas is to develop efficient methods for generating, processing, analyzing, and visualizing large amount of 3D data. Triangular meshes constitute a flexible representation of sampled points that are not regularly distributed in space, such that the model can be adaptively adjusted to the data density. The choice of metrics for building the triangular meshes is crucial to produce high quality models. This paper proposes and evaluates different measures to incrementally refine a Delaunay triangular mesh for image surface approximation until either a certain accuracy is obtained or a maximum number of iterations is achieved. Experiments on several data sets are performed to compare the quality of the resulting meshes.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"49 1","pages":"71-82"},"PeriodicalIF":0.9,"publicationDate":"2018-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79389977","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 detailed overview of the 22 contributions, published in volume 36 (2017) of Image Analysis & Stereology (IAS), is presented. Most of the contributions are relatively interdisciplinary, however, they can be assigned to the following fields of study: computer vision (2), image analysis (2), materials science (3), medical imaging (3), stereology (8) and stohastic geometry (2). In addition, two editorials were published, while four of the contributions in the field of stereology are review papers for the special topic "The History of Stereology". It can be concluded that the readership was offered with a large variety of topics within the broader multidisciplinary field of stereology and image analysis, therefore reflecting the scope of IAS.
{"title":"IMAGE ANALYSIS & STEREOLOGY: 2017 RESEARCH HIGHLIGHTS","authors":"T. Vrtovec","doi":"10.5566/IAS.1916","DOIUrl":"https://doi.org/10.5566/IAS.1916","url":null,"abstract":"A detailed overview of the 22 contributions, published in volume 36 (2017) of Image Analysis & Stereology (IAS), is presented. Most of the contributions are relatively interdisciplinary, however, they can be assigned to the following fields of study: computer vision (2), image analysis (2), materials science (3), medical imaging (3), stereology (8) and stohastic geometry (2). In addition, two editorials were published, while four of the contributions in the field of stereology are review papers for the special topic \"The History of Stereology\". It can be concluded that the readership was offered with a large variety of topics within the broader multidisciplinary field of stereology and image analysis, therefore reflecting the scope of IAS.","PeriodicalId":49062,"journal":{"name":"Image Analysis & Stereology","volume":"35 2 1","pages":"1-7"},"PeriodicalIF":0.9,"publicationDate":"2018-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78022951","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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