In this paper, an adapted unsupervised segmentation approach is proposed to fully automate the segmentation of white blood cells and their nuclei. Segmentation and counting of white blood cells from microscope images ...
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ISBN:
(数字)9781728163031
ISBN:
(纸本)9781728163048
In this paper, an adapted unsupervised segmentation approach is proposed to fully automate the segmentation of white blood cells and their nuclei. Segmentation and counting of white blood cells from microscope images are challenging tasks, especially the segmentation of white blood cell nuclei from the cell wall and cytoplasm because of the need to consider intra-class variations arising from non-uniform illumination, stage of maturity, colour distribution, scale, and overlapped cells with other components of the blood. We propose the use of the JSEG algorithm based on colour-texture distribution, and adapted region growing using the Fuzzy C Mean to segment and count WBCs and their nuclei. First, colours in the image are quantized to represent differentiated regions in the image. Image pixel colours are then replaced by their corresponding colour class labels, thus forming a class-map of the image. A criterion for “good” segmentation using this spatial class-map is applied to local image windows resulting in J-images, which can be segmented using adapted region growing based on the Fuzzy C Mean algorithm. The Fuzzy C Mean is also employed for counting each white blood cell in images. Performance of the proposed method is evaluated on a combined dataset of 10 types of white blood cell with 200 digital images collected from 3 datasets. It achieves an average segmentation accuracy using four indices for WBC segmentation: jaccard distance, rand index, boundary detection error and F-value indices, 0.002, 0.93, 10.11, 0.93, respectively, while for WBC nuclei segmentation, it achieves indices values, 0.015, 0.88, 14.11, 0.90, respectively. The segmentation accuracy of the proposed method is also compared and benchmarked with the other existing techniques for segmentation of white blood cells over the same datasets and the results show that the proposed method is superior to other approaches.
Grey Model is a useful method for forecasting with limited data and has been widely used in a great variety of disciplines. This study gives a briefy review of the operation of grey prediction, and then use the GM(1,1...
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The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th pacific-asiaconference on Knowledge Discovery and data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023.;Th...
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ISBN:
(数字)9783031333743
ISBN:
(纸本)9783031333736
The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th pacific-asiaconference on Knowledge Discovery and data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023.;The 143 papers presented in these proceedings were carefully reviewed and selected from 813 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th pacific-asiaconference on Knowledge Discovery and data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023.;Th...
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ISBN:
(数字)9783031333835
ISBN:
(纸本)9783031333828
The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th pacific-asiaconference on Knowledge Discovery and data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023.;The 143 papers presented in these proceedings were carefully reviewed and selected from 813 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th pacific-asiaconference on Knowledge Discovery and data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023.;Th...
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ISBN:
(数字)9783031333804
ISBN:
(纸本)9783031333798
The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th pacific-asiaconference on Knowledge Discovery and data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023.;The 143 papers presented in these proceedings were carefully reviewed and selected from 813 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th pacific-asiaconference on Knowledge Discovery and data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023.;Th...
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ISBN:
(数字)9783031333774
ISBN:
(纸本)9783031333767
The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th pacific-asiaconference on Knowledge Discovery and data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023.;The 143 papers presented in these proceedings were carefully reviewed and selected from 813 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
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