Development of a computerized system for cytogenetic analysis and classification

Pantaleao, C.H.Z.; Azevedo, Filipe; Pereira, Eanes Torres; Ribeiro, M.C.M.; Marques, Jefferson Luiz Brum

doi:10.1109/iembs.2002.1053245

Cited by 4 publications

(1 citation statement)

References 3 publications

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“…The typical case error rate was approximately 20% [47]. If the chromosomes were touching, overlapping or deformed as shown in the majority of images acquired in the clinical laboratories, the classification error rate was substantially increased [52]. Third, although there are several publicly available databases of chromosome images (i.e.…”

Section: Discussionmentioning

confidence: 99%

Development and evaluation of automated systems for detection and classification of banded chromosomes: current status and future perspectives

Wang

Zheng

Wood

et al. 2005

J. Phys. D: Appl. Phys.

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Automated detection and classification of banded chromosomes may help clinicians diagnose cancers and other genetic disorders at an early stage more efficiently and accurately. However, developing such an automated system (including both a high-speed microscopic image scanning device and related computer-assisted schemes) is quite a challenging and difficult task. Since the 1980s, great research efforts have been made to develop fast and more reliable methods to assist clinical technicians in performing this important and time-consuming task. A number of computer-assisted methods including classical statistical methods, artificial neural networks and knowledge-based fuzzy logic systems, have been applied and tested. Based on the initial test using limited datasets, encouraging results in algorithm and system development have been demonstrated. Despite the significant research effort and progress made over the last two decades, computer-assisted chromosome detection and classification systems have not been routinely accepted and used in clinical laboratories. Further research and development is needed.

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Section: Discussionmentioning

confidence: 99%

Development and evaluation of automated systems for detection and classification of banded chromosomes: current status and future perspectives

Wang

Zheng

Wood

et al. 2005

J. Phys. D: Appl. Phys.

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A novel approach for efficient extrication of overlapping chromosomes in automated karyotyping

Munot¹,

Mukherjee

Joshi³

2013

Med Biol Eng Comput

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Since the introduction of the automated karyotyping systems, segmentation and classification of touching and overlapping chromosomes in the metaphase images are major challenges. The earlier reported techniques for disentangling the chromosome overlaps have limited success and use only color information in case of multispectral imaging. Most of them are restricted to separation of single overlap of two chromosomes. This paper introduces a novel algorithm to extricate overlapping chromosomes in a metaphase image. The proposed technique uses Delaunay triangulation to automatically identify the number of overlaps in a cluster followed by the detection of the appropriate cut-points. The banding information on the overlapped region further resolves the set of overlapping chromosomes with the identified cut-points. The proposed algorithm has been tested with four data sets of 60 overlapping cases, obtained from publically available databases and private genetic labs. The experimental results provide an overall accuracy of 75–100 % for resolving the cluster of 1–6 overlaps.

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A Watershed Based Segmentation Method for Overlapping Chromosome Images

Wan

Feng

2010

2010 Second International Workshop on Education Technology and Computer Science

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Development of a computerized system for cytogenetic analysis and classification

Cited by 4 publications

References 3 publications

Development and evaluation of automated systems for detection and classification of banded chromosomes: current status and future perspectives

Development and evaluation of automated systems for detection and classification of banded chromosomes: current status and future perspectives

A novel approach for efficient extrication of overlapping chromosomes in automated karyotyping

A Watershed Based Segmentation Method for Overlapping Chromosome Images

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