The Experts below are selected from a list of 291 Experts worldwide ranked by ideXlab platform
Peter K Rogan - One of the best experts on this subject based on the ideXlab platform.
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centromere detection of human Metaphase Chromosome images using a candidate based method
F1000Research, 2016Co-Authors: Akila Subasinghe, Jagath Samarabandu, Yanxin Li, Ruth C Wilkins, Farrah Flegal, Joan H M Knoll, Peter K RoganAbstract:Accurate detection of the human Metaphase Chromosome centromere is a critical element of cytogenetic diagnostic techniques, including Chromosome enumeration, karyotyping and radiation biodosimetry. Existing centromere detection methods tends to perform poorly in the presence of irregular boundaries, shape variations and premature sister chromatid separation. We present a centromere detection algorithm that uses a novel contour partitioning technique to generate centromere candidates followed by a machine learning approach to select the best candidate that enhances the detection accuracy. The contour partitioning technique evaluates various combinations of salient points along the Chromosome boundary using a novel feature set and is able to identify telomere regions as well as detect and correct for sister chromatid separation. This partitioning is used to generate a set of centromere candidates which are then evaluated based on a second set of proposed features. The proposed algorithm outperforms previously published algorithms and is shown to do so with a larger set of Chromosome images. A highlight of the proposed algorithm is the ability to rank this set of centromere candidates and create a centromere confidence metric which may be used in post-detection analysis. When tested with a larger Metaphase Chromosome database consisting of 1400 Chromosomes collected from 40 Metaphase cell images, the proposed algorithm was able to accurately localize 1220 centromere locations yielding a detection accuracy of 87%.
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centromere detection of human Metaphase Chromosome images using a candidate based method
bioRxiv, 2015Co-Authors: Akila Subasinghe, Jagath Samarabandu, Yanxin Li, Ruth C Wilkins, Farrah Flegal, Joan H M Knoll, Peter K RoganAbstract:Accurate detection of the human Metaphase Chromosome centromere is an critical element of cytogenetic diagnostic techniques, including Chromosome enumeration, karyotyping and radiation biodosimetry. Existing image processing methods can perform poorly in the presence of irregular boundaries, shape variations and premature sister chromatid separation, which can adversely affect centromere localization. We present a centromere detection algorithm that uses a novel profile thickness measurement technique on irregular Chromosome structures defined by contour partitioning. Our algorithm generates a set of centromere candidates which are then evaluated based on a set of features derived from images of Chromosomes. Our method also partitions the Chromosome contour to isolate its telomere regions and then detects and corrects for sister chromatid separation. When tested with a Chromosome database consisting of 1400 Chromosomes collected from 40 Metaphase cell images, the candidate based centromere detection algorithm was able to accurately localize 1220 centromere locations yielding a detection accuracy of 87%. We also introduce a Candidate Based Centromere Confidence (CBCC) metric which indicates an approximate confidence value of a given centromere detection and can be readily extended into other candidate related detection problems.
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Intensity Integrated Laplacian-Based Thickness Measurement for Detecting Human Metaphase Chromosome Centromere Location
IEEE Transactions on Biomedical Engineering, 2013Co-Authors: Akila Subasinghe Arachchige, Jagath Samarabandu, Joan H M Knoll, Peter K RoganAbstract:Accurate detection of the human Metaphase Chromosome centromere is an important step in many Chromosome analysis and medical diagnosis algorithms. The centromere location can be utilized to derive information such as the Chromosome type, polarity assignment, etc. Methods available in the literature yield unreliable results mainly due to high variability of morphology in Metaphase Chromosomes and boundary noise present in the image. In this paper, we have proposed a multistaged algorithm which includes the use of discrete curve evolution, gradient vector flow active contours, functional approximation of curve segments, and support vector machine classification. The standard Laplacian thickness measurement algorithm was enhanced to incorporate both contour information as well as intensity information to obtain a more accurate centromere location. In addition to segmentation and width profile measurement, the proposed algorithm can also correct for sister chromatid separation in cell images. The proposed method was observed to be more accurate and statistically significant as compared to a centerline-based method when tested with 226 human Metaphase Chromosomes.
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CCECE - Intensity integrated Laplacian algorithm for human Metaphase Chromosome centromere detection
2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2012Co-Authors: Akila Subasinghe Arachchige, Jagath Samarabandu, Peter K Rogan, Joan H M KnollAbstract:Centromere localization in human Metaphase Chromosomes is an essential task in many cytogenetic diagnosis procedures. The centromere location can be utilized to derive information such as the Chromosome type, polarity assignment etc. Methods available in literature yield unreliable results mainly due to high variability of morphology in Metaphase Chromosomes and boundary noise in the image. In this paper we have proposed a multi-staged algorithm which utilizes both contour information as well as intensity information to obtain a more accurate centromere location. The width information along the axis of symmetry is obtained using a novel Laplacian based thickness measurement algorithm. The proposed method was observed to be more accurate compared to the state of the art when tested with 226 human Metaphase Chromosomes.
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Intensity integrated Laplacian algorithm for human Metaphase Chromosome centromere detection
2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2012Co-Authors: Akila Subasinghe Arachchige, Jagath Samarabandu, Peter K Rogan, Joan H M KnollAbstract:Centromere localization in human Metaphase Chromosomes is an essential task in many cytogenetic diagnosis procedures. The centromere location can be utilized to derive information such as the Chromosome type, polarity assignment etc. Methods available in literature yield unreliable results mainly due to high variability of morphology in Metaphase Chromosomes and boundary noise in the image. In this paper we have proposed a multi-staged algorithm which utilizes both contour information as well as intensity information to obtain a more accurate centromere location. The width information along the axis of symmetry is obtained using a novel Laplacian based thickness measurement algorithm. The proposed method was observed to be more accurate compared to the state of the art when tested with 226 human Metaphase Chromosomes.
Joanramon Daban - One of the best experts on this subject based on the ideXlab platform.
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electron microscopy and atomic force microscopy studies of chromatin and Metaphase Chromosome structure
Micron, 2011Co-Authors: Joanramon DabanAbstract:Abstract The folding of the chromatin filament and, in particular, the organization of genomic DNA within Metaphase Chromosomes has attracted the interest of many laboratories during the last five decades. This review discusses our current understanding of chromatin higher-order structure based on results obtained with transmission electron microscopy (TEM), cryo-electron microscopy (cryo-EM), and different atomic force microscopy (AFM) techniques. Chromatin isolated from different cell types in buffers without cations form extended filaments with nucleosomes visible as separated units. In presence of low concentrations of Mg 2+ , chromatin filaments are folded into fibers having a diameter of ∼30 nm. Highly compact fibers were obtained with isolated chromatin fragments in solutions containing 1–2 mM Mg 2+ . The high density of these fibers suggested that the successive turns of the chromatin filament are interdigitated. Similar results were obtained with reconstituted nucleosome arrays under the same ionic conditions. This led to the proposal of compact interdigitated solenoid models having a helical pitch of 4–5 nm. These findings, together with the observation of columns of stacked nucleosomes in different liquid crystal phases formed by aggregation of nucleosome core particles at high concentration, and different experimental evidences obtained using other approaches, indicate that face-to-face interactions between nucleosomes are very important for the formation of dense chromatin structures. Chromatin fibers were observed in Metaphase Chromosome preparations in deionized water and in buffers containing EDTA, but Chromosomes in presence of the Mg 2+ concentrations found in Metaphase (5–22 mM) are very compact, without visible fibers. Moreover, a recent cryo-electron microscopy analysis of vitreous sections of mitotic cells indicated that chromatin has a disordered organization, which does not support the existence of 30-nm fibers in condensed Chromosomes. TEM images of partially denatured Chromosomes obtained using different procedures that maintain the ionic conditions of Metaphase showed that bulk chromatin in Chromosomes is organized forming multilayered plate-like structures. The structure and mechanical properties of these plates were studied using cryo-EM, electron tomography, AFM imaging in aqueous media, and AFM-based nanotribology and force spectroscopy. The results obtained indicated that the chromatin filament forms a flexible two-dimensional network, in which DNA is the main component responsible for the mechanical strength observed in friction force measurements. The discovery of this unexpected structure based on a planar geometry has opened completely new possibilities for the understanding of chromatin folding in Metaphase Chromosomes. It was proposed that chromatids are formed by many stacked thin chromatin plates oriented perpendicular to the chromatid axis. Different experimental evidences indicated that nucleosomes in the plates are irregularly oriented, and that the successive layers are interdigitated (the apparent layer thickness is 5–6 nm), allowing face-to-face interactions between nucleosomes of adjacent layers. The high density of this structure is in agreement with the high concentration of DNA observed in Metaphase Chromosomes of different species, and the irregular orientation of nucleosomes within the plates make these results compatible with those obtained with mitotic cell cryo-sections. The multilaminar chromatin structure proposed for Chromosomes allows an easy explanation of Chromosome banding and of the band splitting observed in stretched Chromosomes.
Xiaodong Chen - One of the best experts on this subject based on the ideXlab platform.
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evaluations of auto focusing methods under a microscopic imaging modality for Metaphase Chromosome image analysis
Analytical Cellular Pathology, 2013Co-Authors: Xiaodong Chen, Yuhua Li, Bin Zheng, Wei R Chen, Shibo LiAbstract:Background: Auto-focusing is an important operation in high throughput imaging scanning. Although many auto-focusing methods have been developed and tested for a variety of imaging modalities, few investigations have been performed on the selection of an optimal auto-focusing method that is suitable for the pathological Metaphase Chromosome analysis under a high resolution scanning microscopic system.
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automated identification of abnormal Metaphase Chromosome cells for the detection of chronic myeloid leukemia using microscopic images
Journal of Biomedical Optics, 2010Co-Authors: Xingwei Wang, Shibo Li, Bin Zheng, John J Mulvihill, Xiaodong ChenAbstract:Karyotyping is an important process to classify Chromosomes into standard classes and the results are routinely used by the clinicians to diagnose cancers and genetic diseases. However, visual karyotyping using microscopic images is time-consuming and tedious, which reduces the diagnostic efficiency and accuracy. Although many efforts have been made to develop computerized schemes for automated karyotyping, no schemes can get be performed without substantial human intervention. Instead of developing a method to classify all Chromosome classes, we develop an automatic scheme to detect abnormal Metaphase cells by identifying a specific class of Chromosomes (class 22) and prescreen for suspicious chronic myeloid leukemia (CML). The scheme includes three steps: (1) iteratively segment randomly distributed individual Chromosomes, (2) process segmented Chromosomes and compute image features to identify the candidates, and (3) apply an adaptive matching template to identify Chromosomes of class 22. An image data set of 451 Metaphase cells extracted from bone marrow specimens of 30 positive and 30 negative cases for CML is selected to test the scheme's performance. The overall case-based classification accuracy is 93.3% (100% sensitivity and 86.7% specificity). The results demonstrate the feasibility of applying an automated scheme to detect or prescreen the suspicious cancer cases.
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automated detection of analyzable Metaphase Chromosome cells depicted on scanned digital microscopic images
Proceedings of SPIE, 2010Co-Authors: Xingwei Wang, Xiaodong Chen, Yuhua Li, Shibo Li, Bin ZhengAbstract:Visually searching for analyzable Metaphase Chromosome cells under microscopes is quite time-consuming and difficult. To improve detection efficiency, consistency, and diagnostic accuracy, an automated microscopic image scanning system was developed and tested to directly acquire digital images with sufficient spatial resolution for clinical diagnosis. A computer-aided detection (CAD) scheme was also developed and integrated into the image scanning system to search for and detect the regions of interest (ROI) that contain analyzable Metaphase Chromosome cells in the large volume of scanned images acquired from one specimen. Thus, the cytogeneticists only need to observe and interpret the limited number of ROIs. In this study, the high-resolution microscopic image scanning and CAD performance was investigated and evaluated using nine sets of images scanned from either bone marrow (three) or blood (six) specimens for diagnosis of leukemia. The automated CAD-selection results were compared with the visual selection. In the experiment, the cytogeneticists first visually searched for the analyzable Metaphase Chromosome cells from specimens under microscopes. The specimens were also automated scanned and followed by applying the CAD scheme to detect and save ROIs containing analyzable cells while deleting the others. The automated selected ROIs were then examined by a panel of three cytogeneticists. From the scanned images, CAD selected more analyzable cells than initially visual examinations of the cytogeneticists in both blood and bone marrow specimens. In general, CAD had higher performance in analyzing blood specimens. Even in three bone marrow specimens, CAD selected 50, 22, 9 ROIs, respectively. Except matching with the initially visual selection of 9, 7, and 5 analyzable cells in these three specimens, the cytogeneticists also selected 41, 15 and 4 new analyzable cells, which were missed in initially visual searching. This experiment showed the feasibility of applying this CAD-guided high-resolution microscopic image scanning system to prescreen and select ROIs that may contain analyzable Metaphase Chromosome cells. The success and the further improvement of this automated scanning system may have great impact on the future clinical practice in genetic laboratories to detect and diagnose diseases.
Jagath Samarabandu - One of the best experts on this subject based on the ideXlab platform.
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centromere detection of human Metaphase Chromosome images using a candidate based method
F1000Research, 2016Co-Authors: Akila Subasinghe, Jagath Samarabandu, Yanxin Li, Ruth C Wilkins, Farrah Flegal, Joan H M Knoll, Peter K RoganAbstract:Accurate detection of the human Metaphase Chromosome centromere is a critical element of cytogenetic diagnostic techniques, including Chromosome enumeration, karyotyping and radiation biodosimetry. Existing centromere detection methods tends to perform poorly in the presence of irregular boundaries, shape variations and premature sister chromatid separation. We present a centromere detection algorithm that uses a novel contour partitioning technique to generate centromere candidates followed by a machine learning approach to select the best candidate that enhances the detection accuracy. The contour partitioning technique evaluates various combinations of salient points along the Chromosome boundary using a novel feature set and is able to identify telomere regions as well as detect and correct for sister chromatid separation. This partitioning is used to generate a set of centromere candidates which are then evaluated based on a second set of proposed features. The proposed algorithm outperforms previously published algorithms and is shown to do so with a larger set of Chromosome images. A highlight of the proposed algorithm is the ability to rank this set of centromere candidates and create a centromere confidence metric which may be used in post-detection analysis. When tested with a larger Metaphase Chromosome database consisting of 1400 Chromosomes collected from 40 Metaphase cell images, the proposed algorithm was able to accurately localize 1220 centromere locations yielding a detection accuracy of 87%.
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centromere detection of human Metaphase Chromosome images using a candidate based method
bioRxiv, 2015Co-Authors: Akila Subasinghe, Jagath Samarabandu, Yanxin Li, Ruth C Wilkins, Farrah Flegal, Joan H M Knoll, Peter K RoganAbstract:Accurate detection of the human Metaphase Chromosome centromere is an critical element of cytogenetic diagnostic techniques, including Chromosome enumeration, karyotyping and radiation biodosimetry. Existing image processing methods can perform poorly in the presence of irregular boundaries, shape variations and premature sister chromatid separation, which can adversely affect centromere localization. We present a centromere detection algorithm that uses a novel profile thickness measurement technique on irregular Chromosome structures defined by contour partitioning. Our algorithm generates a set of centromere candidates which are then evaluated based on a set of features derived from images of Chromosomes. Our method also partitions the Chromosome contour to isolate its telomere regions and then detects and corrects for sister chromatid separation. When tested with a Chromosome database consisting of 1400 Chromosomes collected from 40 Metaphase cell images, the candidate based centromere detection algorithm was able to accurately localize 1220 centromere locations yielding a detection accuracy of 87%. We also introduce a Candidate Based Centromere Confidence (CBCC) metric which indicates an approximate confidence value of a given centromere detection and can be readily extended into other candidate related detection problems.
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Intensity Integrated Laplacian-Based Thickness Measurement for Detecting Human Metaphase Chromosome Centromere Location
IEEE Transactions on Biomedical Engineering, 2013Co-Authors: Akila Subasinghe Arachchige, Jagath Samarabandu, Joan H M Knoll, Peter K RoganAbstract:Accurate detection of the human Metaphase Chromosome centromere is an important step in many Chromosome analysis and medical diagnosis algorithms. The centromere location can be utilized to derive information such as the Chromosome type, polarity assignment, etc. Methods available in the literature yield unreliable results mainly due to high variability of morphology in Metaphase Chromosomes and boundary noise present in the image. In this paper, we have proposed a multistaged algorithm which includes the use of discrete curve evolution, gradient vector flow active contours, functional approximation of curve segments, and support vector machine classification. The standard Laplacian thickness measurement algorithm was enhanced to incorporate both contour information as well as intensity information to obtain a more accurate centromere location. In addition to segmentation and width profile measurement, the proposed algorithm can also correct for sister chromatid separation in cell images. The proposed method was observed to be more accurate and statistically significant as compared to a centerline-based method when tested with 226 human Metaphase Chromosomes.
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CCECE - Intensity integrated Laplacian algorithm for human Metaphase Chromosome centromere detection
2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2012Co-Authors: Akila Subasinghe Arachchige, Jagath Samarabandu, Peter K Rogan, Joan H M KnollAbstract:Centromere localization in human Metaphase Chromosomes is an essential task in many cytogenetic diagnosis procedures. The centromere location can be utilized to derive information such as the Chromosome type, polarity assignment etc. Methods available in literature yield unreliable results mainly due to high variability of morphology in Metaphase Chromosomes and boundary noise in the image. In this paper we have proposed a multi-staged algorithm which utilizes both contour information as well as intensity information to obtain a more accurate centromere location. The width information along the axis of symmetry is obtained using a novel Laplacian based thickness measurement algorithm. The proposed method was observed to be more accurate compared to the state of the art when tested with 226 human Metaphase Chromosomes.
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Intensity integrated Laplacian algorithm for human Metaphase Chromosome centromere detection
2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2012Co-Authors: Akila Subasinghe Arachchige, Jagath Samarabandu, Peter K Rogan, Joan H M KnollAbstract:Centromere localization in human Metaphase Chromosomes is an essential task in many cytogenetic diagnosis procedures. The centromere location can be utilized to derive information such as the Chromosome type, polarity assignment etc. Methods available in literature yield unreliable results mainly due to high variability of morphology in Metaphase Chromosomes and boundary noise in the image. In this paper we have proposed a multi-staged algorithm which utilizes both contour information as well as intensity information to obtain a more accurate centromere location. The width information along the axis of symmetry is obtained using a novel Laplacian based thickness measurement algorithm. The proposed method was observed to be more accurate compared to the state of the art when tested with 226 human Metaphase Chromosomes.
Joan H M Knoll - One of the best experts on this subject based on the ideXlab platform.
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centromere detection of human Metaphase Chromosome images using a candidate based method
F1000Research, 2016Co-Authors: Akila Subasinghe, Jagath Samarabandu, Yanxin Li, Ruth C Wilkins, Farrah Flegal, Joan H M Knoll, Peter K RoganAbstract:Accurate detection of the human Metaphase Chromosome centromere is a critical element of cytogenetic diagnostic techniques, including Chromosome enumeration, karyotyping and radiation biodosimetry. Existing centromere detection methods tends to perform poorly in the presence of irregular boundaries, shape variations and premature sister chromatid separation. We present a centromere detection algorithm that uses a novel contour partitioning technique to generate centromere candidates followed by a machine learning approach to select the best candidate that enhances the detection accuracy. The contour partitioning technique evaluates various combinations of salient points along the Chromosome boundary using a novel feature set and is able to identify telomere regions as well as detect and correct for sister chromatid separation. This partitioning is used to generate a set of centromere candidates which are then evaluated based on a second set of proposed features. The proposed algorithm outperforms previously published algorithms and is shown to do so with a larger set of Chromosome images. A highlight of the proposed algorithm is the ability to rank this set of centromere candidates and create a centromere confidence metric which may be used in post-detection analysis. When tested with a larger Metaphase Chromosome database consisting of 1400 Chromosomes collected from 40 Metaphase cell images, the proposed algorithm was able to accurately localize 1220 centromere locations yielding a detection accuracy of 87%.
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centromere detection of human Metaphase Chromosome images using a candidate based method
bioRxiv, 2015Co-Authors: Akila Subasinghe, Jagath Samarabandu, Yanxin Li, Ruth C Wilkins, Farrah Flegal, Joan H M Knoll, Peter K RoganAbstract:Accurate detection of the human Metaphase Chromosome centromere is an critical element of cytogenetic diagnostic techniques, including Chromosome enumeration, karyotyping and radiation biodosimetry. Existing image processing methods can perform poorly in the presence of irregular boundaries, shape variations and premature sister chromatid separation, which can adversely affect centromere localization. We present a centromere detection algorithm that uses a novel profile thickness measurement technique on irregular Chromosome structures defined by contour partitioning. Our algorithm generates a set of centromere candidates which are then evaluated based on a set of features derived from images of Chromosomes. Our method also partitions the Chromosome contour to isolate its telomere regions and then detects and corrects for sister chromatid separation. When tested with a Chromosome database consisting of 1400 Chromosomes collected from 40 Metaphase cell images, the candidate based centromere detection algorithm was able to accurately localize 1220 centromere locations yielding a detection accuracy of 87%. We also introduce a Candidate Based Centromere Confidence (CBCC) metric which indicates an approximate confidence value of a given centromere detection and can be readily extended into other candidate related detection problems.
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Intensity Integrated Laplacian-Based Thickness Measurement for Detecting Human Metaphase Chromosome Centromere Location
IEEE Transactions on Biomedical Engineering, 2013Co-Authors: Akila Subasinghe Arachchige, Jagath Samarabandu, Joan H M Knoll, Peter K RoganAbstract:Accurate detection of the human Metaphase Chromosome centromere is an important step in many Chromosome analysis and medical diagnosis algorithms. The centromere location can be utilized to derive information such as the Chromosome type, polarity assignment, etc. Methods available in the literature yield unreliable results mainly due to high variability of morphology in Metaphase Chromosomes and boundary noise present in the image. In this paper, we have proposed a multistaged algorithm which includes the use of discrete curve evolution, gradient vector flow active contours, functional approximation of curve segments, and support vector machine classification. The standard Laplacian thickness measurement algorithm was enhanced to incorporate both contour information as well as intensity information to obtain a more accurate centromere location. In addition to segmentation and width profile measurement, the proposed algorithm can also correct for sister chromatid separation in cell images. The proposed method was observed to be more accurate and statistically significant as compared to a centerline-based method when tested with 226 human Metaphase Chromosomes.
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CCECE - Intensity integrated Laplacian algorithm for human Metaphase Chromosome centromere detection
2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2012Co-Authors: Akila Subasinghe Arachchige, Jagath Samarabandu, Peter K Rogan, Joan H M KnollAbstract:Centromere localization in human Metaphase Chromosomes is an essential task in many cytogenetic diagnosis procedures. The centromere location can be utilized to derive information such as the Chromosome type, polarity assignment etc. Methods available in literature yield unreliable results mainly due to high variability of morphology in Metaphase Chromosomes and boundary noise in the image. In this paper we have proposed a multi-staged algorithm which utilizes both contour information as well as intensity information to obtain a more accurate centromere location. The width information along the axis of symmetry is obtained using a novel Laplacian based thickness measurement algorithm. The proposed method was observed to be more accurate compared to the state of the art when tested with 226 human Metaphase Chromosomes.
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Intensity integrated Laplacian algorithm for human Metaphase Chromosome centromere detection
2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2012Co-Authors: Akila Subasinghe Arachchige, Jagath Samarabandu, Peter K Rogan, Joan H M KnollAbstract:Centromere localization in human Metaphase Chromosomes is an essential task in many cytogenetic diagnosis procedures. The centromere location can be utilized to derive information such as the Chromosome type, polarity assignment etc. Methods available in literature yield unreliable results mainly due to high variability of morphology in Metaphase Chromosomes and boundary noise in the image. In this paper we have proposed a multi-staged algorithm which utilizes both contour information as well as intensity information to obtain a more accurate centromere location. The width information along the axis of symmetry is obtained using a novel Laplacian based thickness measurement algorithm. The proposed method was observed to be more accurate compared to the state of the art when tested with 226 human Metaphase Chromosomes.