Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology

Screening and diagnosing of abnormal Leukocytes are crucial for the diagnosis of immune diseases and Acute Lymphoblastic Leukemia (ALL). As the deterioration of abnormal leukocytes is mainly due to the changes in the chromatin distribution, which significantly affects the absorption and reflection o...
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Autor*in:	Xueqi Hu [verfasserIn] Jiahua Ou [verfasserIn] Mei Zhou [verfasserIn] Menghan Hu [verfasserIn] Li Sun [verfasserIn] Song Qiu [verfasserIn] Qingli Li [verfasserIn] Junhao Chu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	leukocyte microscopic hyperspectral imaging nucleus segmentation acute lymphoblastic leukemia

Übergeordnetes Werk:	In: Journal of Innovative Optical Health Sciences - World Scientific Publishing, 2017, 13(2020), 2, Seite 2050005-1-2050005-13
Übergeordnetes Werk:	volume:13 ; year:2020 ; number:2 ; pages:2050005-1-2050005-13

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.1142/S1793545820500054

Katalog-ID:	DOAJ003138666

Internformat


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520			\|a Screening and diagnosing of abnormal Leukocytes are crucial for the diagnosis of immune diseases and Acute Lymphoblastic Leukemia (ALL). As the deterioration of abnormal leukocytes is mainly due to the changes in the chromatin distribution, which significantly affects the absorption and reflection of light, the spectral feature is proved to be important for leukocytes classification and identification. This paper proposes an accurate identification method for healthy and abnormal leukocytes based on microscopic hyperspectral imaging (HSI) technology which combines the spectral information. The segmentation of nucleus and cytoplasm is obtained by the morphological watershed algorithm. Then, the spectral features are extracted and combined with the spatial features. Based on this, the support vector machine (SVM) is applied for classification of five types of leukocytes and abnormal leukocytes. Compared with different classification methods, the proposed method utilizes spectral features which highlight the differences between healthy leukocytes and abnormal leukocytes, improving the accuracy in the classification and identification of leukocytes. This paper only selects one subtype of ALL for test, and the proposed method can be applied for detection of other leukemia in the future.
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allfields	10.1142/S1793545820500054 doi (DE-627)DOAJ003138666 (DE-599)DOAJf76edc2ba1ee4085aac6b63d168f64ac DE-627 ger DE-627 rakwb eng QC350-467 Xueqi Hu verfasserin aut Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Screening and diagnosing of abnormal Leukocytes are crucial for the diagnosis of immune diseases and Acute Lymphoblastic Leukemia (ALL). As the deterioration of abnormal leukocytes is mainly due to the changes in the chromatin distribution, which significantly affects the absorption and reflection of light, the spectral feature is proved to be important for leukocytes classification and identification. This paper proposes an accurate identification method for healthy and abnormal leukocytes based on microscopic hyperspectral imaging (HSI) technology which combines the spectral information. The segmentation of nucleus and cytoplasm is obtained by the morphological watershed algorithm. Then, the spectral features are extracted and combined with the spatial features. Based on this, the support vector machine (SVM) is applied for classification of five types of leukocytes and abnormal leukocytes. Compared with different classification methods, the proposed method utilizes spectral features which highlight the differences between healthy leukocytes and abnormal leukocytes, improving the accuracy in the classification and identification of leukocytes. This paper only selects one subtype of ALL for test, and the proposed method can be applied for detection of other leukemia in the future. leukocyte microscopic hyperspectral imaging nucleus segmentation acute lymphoblastic leukemia Technology T Optics. Light Jiahua Ou verfasserin aut Mei Zhou verfasserin aut Menghan Hu verfasserin aut Li Sun verfasserin aut Song Qiu verfasserin aut Qingli Li verfasserin aut Junhao Chu verfasserin aut In Journal of Innovative Optical Health Sciences World Scientific Publishing, 2017 13(2020), 2, Seite 2050005-1-2050005-13 (DE-627)60940315X (DE-600)2515441-2 17937205 nnns volume:13 year:2020 number:2 pages:2050005-1-2050005-13 https://doi.org/10.1142/S1793545820500054 kostenfrei https://doaj.org/article/f76edc2ba1ee4085aac6b63d168f64ac kostenfrei http://www.worldscientific.com/doi/pdf/10.1142/S1793545820500054 kostenfrei https://doaj.org/toc/1793-5458 Journal toc kostenfrei https://doaj.org/toc/1793-7205 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2020 2 2050005-1-2050005-13
spelling	10.1142/S1793545820500054 doi (DE-627)DOAJ003138666 (DE-599)DOAJf76edc2ba1ee4085aac6b63d168f64ac DE-627 ger DE-627 rakwb eng QC350-467 Xueqi Hu verfasserin aut Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Screening and diagnosing of abnormal Leukocytes are crucial for the diagnosis of immune diseases and Acute Lymphoblastic Leukemia (ALL). As the deterioration of abnormal leukocytes is mainly due to the changes in the chromatin distribution, which significantly affects the absorption and reflection of light, the spectral feature is proved to be important for leukocytes classification and identification. This paper proposes an accurate identification method for healthy and abnormal leukocytes based on microscopic hyperspectral imaging (HSI) technology which combines the spectral information. The segmentation of nucleus and cytoplasm is obtained by the morphological watershed algorithm. Then, the spectral features are extracted and combined with the spatial features. Based on this, the support vector machine (SVM) is applied for classification of five types of leukocytes and abnormal leukocytes. Compared with different classification methods, the proposed method utilizes spectral features which highlight the differences between healthy leukocytes and abnormal leukocytes, improving the accuracy in the classification and identification of leukocytes. This paper only selects one subtype of ALL for test, and the proposed method can be applied for detection of other leukemia in the future. leukocyte microscopic hyperspectral imaging nucleus segmentation acute lymphoblastic leukemia Technology T Optics. Light Jiahua Ou verfasserin aut Mei Zhou verfasserin aut Menghan Hu verfasserin aut Li Sun verfasserin aut Song Qiu verfasserin aut Qingli Li verfasserin aut Junhao Chu verfasserin aut In Journal of Innovative Optical Health Sciences World Scientific Publishing, 2017 13(2020), 2, Seite 2050005-1-2050005-13 (DE-627)60940315X (DE-600)2515441-2 17937205 nnns volume:13 year:2020 number:2 pages:2050005-1-2050005-13 https://doi.org/10.1142/S1793545820500054 kostenfrei https://doaj.org/article/f76edc2ba1ee4085aac6b63d168f64ac kostenfrei http://www.worldscientific.com/doi/pdf/10.1142/S1793545820500054 kostenfrei https://doaj.org/toc/1793-5458 Journal toc kostenfrei https://doaj.org/toc/1793-7205 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2020 2 2050005-1-2050005-13
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allfieldsGer	10.1142/S1793545820500054 doi (DE-627)DOAJ003138666 (DE-599)DOAJf76edc2ba1ee4085aac6b63d168f64ac DE-627 ger DE-627 rakwb eng QC350-467 Xueqi Hu verfasserin aut Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Screening and diagnosing of abnormal Leukocytes are crucial for the diagnosis of immune diseases and Acute Lymphoblastic Leukemia (ALL). As the deterioration of abnormal leukocytes is mainly due to the changes in the chromatin distribution, which significantly affects the absorption and reflection of light, the spectral feature is proved to be important for leukocytes classification and identification. This paper proposes an accurate identification method for healthy and abnormal leukocytes based on microscopic hyperspectral imaging (HSI) technology which combines the spectral information. The segmentation of nucleus and cytoplasm is obtained by the morphological watershed algorithm. Then, the spectral features are extracted and combined with the spatial features. Based on this, the support vector machine (SVM) is applied for classification of five types of leukocytes and abnormal leukocytes. Compared with different classification methods, the proposed method utilizes spectral features which highlight the differences between healthy leukocytes and abnormal leukocytes, improving the accuracy in the classification and identification of leukocytes. This paper only selects one subtype of ALL for test, and the proposed method can be applied for detection of other leukemia in the future. leukocyte microscopic hyperspectral imaging nucleus segmentation acute lymphoblastic leukemia Technology T Optics. Light Jiahua Ou verfasserin aut Mei Zhou verfasserin aut Menghan Hu verfasserin aut Li Sun verfasserin aut Song Qiu verfasserin aut Qingli Li verfasserin aut Junhao Chu verfasserin aut In Journal of Innovative Optical Health Sciences World Scientific Publishing, 2017 13(2020), 2, Seite 2050005-1-2050005-13 (DE-627)60940315X (DE-600)2515441-2 17937205 nnns volume:13 year:2020 number:2 pages:2050005-1-2050005-13 https://doi.org/10.1142/S1793545820500054 kostenfrei https://doaj.org/article/f76edc2ba1ee4085aac6b63d168f64ac kostenfrei http://www.worldscientific.com/doi/pdf/10.1142/S1793545820500054 kostenfrei https://doaj.org/toc/1793-5458 Journal toc kostenfrei https://doaj.org/toc/1793-7205 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2020 2 2050005-1-2050005-13
allfieldsSound	10.1142/S1793545820500054 doi (DE-627)DOAJ003138666 (DE-599)DOAJf76edc2ba1ee4085aac6b63d168f64ac DE-627 ger DE-627 rakwb eng QC350-467 Xueqi Hu verfasserin aut Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Screening and diagnosing of abnormal Leukocytes are crucial for the diagnosis of immune diseases and Acute Lymphoblastic Leukemia (ALL). As the deterioration of abnormal leukocytes is mainly due to the changes in the chromatin distribution, which significantly affects the absorption and reflection of light, the spectral feature is proved to be important for leukocytes classification and identification. This paper proposes an accurate identification method for healthy and abnormal leukocytes based on microscopic hyperspectral imaging (HSI) technology which combines the spectral information. The segmentation of nucleus and cytoplasm is obtained by the morphological watershed algorithm. Then, the spectral features are extracted and combined with the spatial features. Based on this, the support vector machine (SVM) is applied for classification of five types of leukocytes and abnormal leukocytes. Compared with different classification methods, the proposed method utilizes spectral features which highlight the differences between healthy leukocytes and abnormal leukocytes, improving the accuracy in the classification and identification of leukocytes. This paper only selects one subtype of ALL for test, and the proposed method can be applied for detection of other leukemia in the future. leukocyte microscopic hyperspectral imaging nucleus segmentation acute lymphoblastic leukemia Technology T Optics. Light Jiahua Ou verfasserin aut Mei Zhou verfasserin aut Menghan Hu verfasserin aut Li Sun verfasserin aut Song Qiu verfasserin aut Qingli Li verfasserin aut Junhao Chu verfasserin aut In Journal of Innovative Optical Health Sciences World Scientific Publishing, 2017 13(2020), 2, Seite 2050005-1-2050005-13 (DE-627)60940315X (DE-600)2515441-2 17937205 nnns volume:13 year:2020 number:2 pages:2050005-1-2050005-13 https://doi.org/10.1142/S1793545820500054 kostenfrei https://doaj.org/article/f76edc2ba1ee4085aac6b63d168f64ac kostenfrei http://www.worldscientific.com/doi/pdf/10.1142/S1793545820500054 kostenfrei https://doaj.org/toc/1793-5458 Journal toc kostenfrei https://doaj.org/toc/1793-7205 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2020 2 2050005-1-2050005-13
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callnumber-first	Q - Science
author	Xueqi Hu
spellingShingle	Xueqi Hu misc QC350-467 misc leukocyte misc microscopic hyperspectral imaging misc nucleus segmentation misc acute lymphoblastic leukemia misc Technology misc T misc Optics. Light Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology
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topic_title	QC350-467 Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology leukocyte microscopic hyperspectral imaging nucleus segmentation acute lymphoblastic leukemia
topic	misc QC350-467 misc leukocyte misc microscopic hyperspectral imaging misc nucleus segmentation misc acute lymphoblastic leukemia misc Technology misc T misc Optics. Light
topic_unstemmed	misc QC350-467 misc leukocyte misc microscopic hyperspectral imaging misc nucleus segmentation misc acute lymphoblastic leukemia misc Technology misc T misc Optics. Light
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title	Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology
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title_full	Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology
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title_sort	spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology
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title_auth	Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology
abstract	Screening and diagnosing of abnormal Leukocytes are crucial for the diagnosis of immune diseases and Acute Lymphoblastic Leukemia (ALL). As the deterioration of abnormal leukocytes is mainly due to the changes in the chromatin distribution, which significantly affects the absorption and reflection of light, the spectral feature is proved to be important for leukocytes classification and identification. This paper proposes an accurate identification method for healthy and abnormal leukocytes based on microscopic hyperspectral imaging (HSI) technology which combines the spectral information. The segmentation of nucleus and cytoplasm is obtained by the morphological watershed algorithm. Then, the spectral features are extracted and combined with the spatial features. Based on this, the support vector machine (SVM) is applied for classification of five types of leukocytes and abnormal leukocytes. Compared with different classification methods, the proposed method utilizes spectral features which highlight the differences between healthy leukocytes and abnormal leukocytes, improving the accuracy in the classification and identification of leukocytes. This paper only selects one subtype of ALL for test, and the proposed method can be applied for detection of other leukemia in the future.
abstractGer	Screening and diagnosing of abnormal Leukocytes are crucial for the diagnosis of immune diseases and Acute Lymphoblastic Leukemia (ALL). As the deterioration of abnormal leukocytes is mainly due to the changes in the chromatin distribution, which significantly affects the absorption and reflection of light, the spectral feature is proved to be important for leukocytes classification and identification. This paper proposes an accurate identification method for healthy and abnormal leukocytes based on microscopic hyperspectral imaging (HSI) technology which combines the spectral information. The segmentation of nucleus and cytoplasm is obtained by the morphological watershed algorithm. Then, the spectral features are extracted and combined with the spatial features. Based on this, the support vector machine (SVM) is applied for classification of five types of leukocytes and abnormal leukocytes. Compared with different classification methods, the proposed method utilizes spectral features which highlight the differences between healthy leukocytes and abnormal leukocytes, improving the accuracy in the classification and identification of leukocytes. This paper only selects one subtype of ALL for test, and the proposed method can be applied for detection of other leukemia in the future.
abstract_unstemmed	Screening and diagnosing of abnormal Leukocytes are crucial for the diagnosis of immune diseases and Acute Lymphoblastic Leukemia (ALL). As the deterioration of abnormal leukocytes is mainly due to the changes in the chromatin distribution, which significantly affects the absorption and reflection of light, the spectral feature is proved to be important for leukocytes classification and identification. This paper proposes an accurate identification method for healthy and abnormal leukocytes based on microscopic hyperspectral imaging (HSI) technology which combines the spectral information. The segmentation of nucleus and cytoplasm is obtained by the morphological watershed algorithm. Then, the spectral features are extracted and combined with the spatial features. Based on this, the support vector machine (SVM) is applied for classification of five types of leukocytes and abnormal leukocytes. Compared with different classification methods, the proposed method utilizes spectral features which highlight the differences between healthy leukocytes and abnormal leukocytes, improving the accuracy in the classification and identification of leukocytes. This paper only selects one subtype of ALL for test, and the proposed method can be applied for detection of other leukemia in the future.
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title_short	Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology
url	https://doi.org/10.1142/S1793545820500054 https://doaj.org/article/f76edc2ba1ee4085aac6b63d168f64ac http://www.worldscientific.com/doi/pdf/10.1142/S1793545820500054 https://doaj.org/toc/1793-5458 https://doaj.org/toc/1793-7205
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up_date	2024-07-03T16:12:25.909Z
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Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology

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