White Blood Cell Segmentation by Distance Mapping Active Contour

Sanpanich, A.; Iampa, Woranut; Pintavirooj, C.; Tosranon, P.

doi:10.1109/iscit.2008.4700193

Cited by 7 publications

(2 citation statements)

References 16 publications

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“…Yang [6] introduced unsupervised robust color GVF snake with L2E robust estimation. Sanpanich [7] estimated cytoplasm roughly based on nucleus convex hull, distance mapping and GVF snake was applied to segment WBC boundary. Obviously, the segmentation method of cytoplasm is much more complex and time-consuming.…”

Section: Introductionmentioning

confidence: 99%

Fast segmentation of white blood cell based on visual salient features

et al. 2011

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This paper presents a fast, precise method for segmenting white blood cell(WBC) based on visual salient features, which is a two-stage algorithm consisting of adaptive WBC location based on salient map(AWLSM) by simulating the process of human perception with bottom-up strategies and extract precise cell structure in cell salient attention window(CASW) using parameter controlled adaptive salient mechanism (PCASM), the first step locates several CASWs in the blood cell image and the second step is to extract nucleus and cytoplasm accurately in each CASW. The experimental results demonstrate that the proposed method has sufficient accuracy and speediness to be used in the automatic blood analyzer.

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Section: Introductionmentioning

confidence: 99%

Fast segmentation of white blood cell based on visual salient features

et al. 2011

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“…Nowadays, the rapid progress of information technology promotes the automatization of blood cells diagnosis based on modern image processing and pattern recognition approaches [10,13]. Among these techniques, automatic segmentation of certain blood cells out of complex scenes should be foremost solved in quantitative analysis of blood cells.…”

Section: Introductionmentioning

confidence: 99%

Leukemic cells segmentation algorithm based on molecular spectral imaging technology

Dai

Liu

et al. 2009

SPIE Proceedings

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A molecular spectral imaging system instead of common microscope was used to capture the spectral images of blood smears. Then an improved spectral angle mapper algorithm for automatic blood cells segmentation was presented. In this algorithm, the spectral vectors of blood cells were normalized first.Then the spectral angles of all bands and partial bands were calculated respectively. Finally, the blood cells were segmented according to the spectral angles combined with the threshold segmentation method. As a case study, the leukemia cells were selected as the target and segmented with the new algorithm. The results demonstrate that this algorithm can utilizes both spectral and spatial information of blood cells and segment the leukemia cells more accurately.

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Automated cervical cancer detection through RGVF segmentation and SVM classification

Sajeena¹,

Jereesh²

2015

2015 International Conference on Computing and Network Communications (CoCoNet)

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White Blood Cell Segmentation by Distance Mapping Active Contour

Cited by 7 publications

References 16 publications

Fast segmentation of white blood cell based on visual salient features

Fast segmentation of white blood cell based on visual salient features

Leukemic cells segmentation algorithm based on molecular spectral imaging technology

Automated cervical cancer detection through RGVF segmentation and SVM classification

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