USER-friendly image-based segmentation and analysis of chromosomes

Uhlmann, Virginie; Delgado-Gonzalo, Ricard; Unser, Michaël; Michel, Pierre; Baldi, Lucia; Wurm, Florian Μ.

doi:10.1109/isbi.2016.7493291

Cited by 8 publications

(4 citation statements)

References 10 publications

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“…Detection . Uhlmann et al 7 developed a tool for segmentation using standard k‐means clustering. Each chromosome is individually segmented and extracted using active contours and bounded rectangles.…”

Section: Literature Reviewmentioning

confidence: 99%

Karyotyping of human chromosomes in metaphase images using faster R‐CNN and inception models

Chavan,

Nair,

Nimbalkar

et al. 2024

Int J Imaging Syst Tech

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Karyotyping is the process of pairing and ordering human chromosomes from metaphase chromosomal images depending on their size, centromere position, and banding patterns. It is used to analyze human chromosomes for various genetic disorders especially during prenatal screenings. Since manual karyotyping is a labor‐intensive and a time‐consuming task, developing an automatic or semi‐automatic computer‐assisted karyotyping system is the need of the hour. The proposed karyotyping system aims to detect human chromosomes (22 pairs of autosomes and one pair of sex chromosome) from the microscopic metaphase images which is followed by separation of overlapped chromosomes. Extracted chromosomes are first classified into seven Denver groups (A to G) followed by classifying individual chromosomes within their Denver group. Then the classified chromosome pairs are used to create a karyotype with the assistance of cytologists or by using estimated chromosome length as cytogenetic parameter. A total of 234 chromosomal images from two different public datasets are used for experimentation. Human chromosomes in the microscopic metaphase images are detected using faster regions with convolutional neural networks (Faster R‐CNN) combined with Inception v2. Then convexity defect algorithm is preferred for separation of overlapped chromosomes. The detected chromosomes are classified using the proposed two‐step approach in which Inception v3 model is used. Then the classified chromosome pairs are used to create a karyotype with the assistance of cytologists or by using estimated chromosome length as cytogenetic parameter. Faster R‐CNN model gives a detection accuracy of 98.53%. Denver group classification with the two‐step approach provides a better accuracy of 84.59% when network is trained for 64 902 epochs. Faster R‐CNN outperforms in detection and works faster as it searches chromosomes within the regional proposals. The two‐step classification approach gives better classification accuracy. The proposed approach also works very well for overlapping chromosomes due to use of convexity defects algorithm. The classified chromosome pairs are useful tools for the cytologists to create a karyotype with minimal efforts.

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Section: Literature Reviewmentioning

confidence: 99%

Karyotyping of human chromosomes in metaphase images using faster R‐CNN and inception models

Chavan,

Nair,

Nimbalkar

et al. 2024

Int J Imaging Syst Tech

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show abstract

“…The results from MATLAB have been validated with the number of chromosomes detected by the ChromosomeJ plugin in ImageJ. ChromosomeJ is an efficient and user-friendly tool for the segmentation of images containing chromosomes or, more generally, rod-shaped elements, that are "spread" on microscopic slides (Uhlmann et al, 2016). For MF detection via ChromosomeJ, the nuclei images were first converted automatically to grayscale images, and the chromosomes were then detected.…”

Section: Image Analysis and Quantification Of Immunohistochemical Feamentioning

confidence: 99%

Epithelial Distribution of E-Cadherin, p63, and Mitotic Figures in ApoTome Images to Determine the Oncogenic Potentiality of Oral Submucous Fibrosis

Nag

Paul²,

Pal³

et al. 2020

Microsc Microanal

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“…Some packages are also published for drawing the idiograms in R such as RIdeogram (Hao et al, 2020) and idiogramFISH (Roa and PC Telles, 2020). Currently, tolls such as MircoMeasure (Reeves, 2001), KaryoType (Altınordu et al, 2016), IdeoKar (Mirzaghaderi and Marzangi, 2015), ChromosomeJ plugin (Uhlmann et al, 2016) and, DRAWID (Kirov et al, 2017) are popularly used for the collection and analysis of cytogenetic data.…”

Section: Introductionmentioning

confidence: 99%

Tools for Drawing Informative Idiograms

Mirzaghaderi

2021

Preprint

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Each species has a typical karyotype, which represents the phenotypic appearance of the somatic chromosomes including number, size, and morphology. Idiogram is a diagrammatic representation of the chromosomes showing their relative size, homologous groups and different cytogenetic landmarks. Chromosomal analysis of cytological preparations is an essential component of many investigations which involves the calculation of karyotypic parameters and generation of idiogram. Although various tools are available for karyotype analysis, here we demonstrate karyotype analysis using our recently developed tool named KaryoMeasure. KaryoMeasure is a semi-automated free and user-friendly karyotype analysis software that facilitates data collection from different digital images of the metaphase chromosome spreads and calculates a wide variety of chromosomal and karyotypic parameters along with the related standard errors. KaryoMeasure draws idiograms of both diploid and allopolyploid species into a vector-based SVG or PDF image file.

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USER-friendly image-based segmentation and analysis of chromosomes

Cited by 8 publications

References 10 publications

Karyotyping of human chromosomes in metaphase images using faster R‐CNN and inception models

Karyotyping of human chromosomes in metaphase images using faster R‐CNN and inception models

Epithelial Distribution of E-Cadherin, p63, and Mitotic Figures in ApoTome Images to Determine the Oncogenic Potentiality of Oral Submucous Fibrosis

Tools for Drawing Informative Idiograms

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