A critical function of flow cytometry is to count the concentration of blood cells,which helps in the diagnosis of certain diseases.However,the bulky nature of commercial flow cytometers makes such tests only availabl...A critical function of flow cytometry is to count the concentration of blood cells,which helps in the diagnosis of certain diseases.However,the bulky nature of commercial flow cytometers makes such tests only available in hospitals or laboratories,hindering the spread of point-of-care testing(POCT),especially in underdeveloped areas.Here,we propose a smart Palm-size Optofluidic Hematology Analyzer based on a miniature fluorescence microscope and a microfluidic platform to lighten the device to improve its portability.This gadget has a dimension of 35×30×80 mm and a mass of 39 g,less than 5%of the weight of commercially available flow cytometers.Additionally,automatic leukocyte concentration detection has been realized through the integration of image processing and leukocyte counting algorithms.We compared the leukocyte concentration measurement between our approach and a hemocytometer using the Passing-Bablok analysis and achieved a correlation coefficient of 0.979.Through Bland-Altman analysis,we obtained the relationship between their differences and mean measurement values and established 95%limits of agreement,ranging from−0.93×10^(3)to 0.94×10^(3)cells/μL.We anticipate that this device can be used widely for monitoring and treating diseases such as HIV and tumors beyond hospitals.展开更多
In fluorescence microscopy,computational algorithms have been developed to suppress noise,enhance contrast,and even enable super-resolution(SR).However,the local quality of the images may vary on multiple scales,and t...In fluorescence microscopy,computational algorithms have been developed to suppress noise,enhance contrast,and even enable super-resolution(SR).However,the local quality of the images may vary on multiple scales,and these differences can lead to misconceptions.Current mapping methods fail to finely estimate the local quality,challenging to associate the SR scale content.Here,we develop a rolling Fourier ring correlation(rFRC)method to evaluate the reconstruction uncertainties down to SR scale.To visually pinpoint regions with low reliability,a filtered rFRC is combined with a modified resolution-scaled error map(RSM),offering a comprehensive and concise map for further examination.We demonstrate their performances on various SR imaging modalities,and the resulting quantitative maps enable better SR images integrated from different reconstructions.Overall,we expect that our framework can become a routinely used tool for biologists in assessing their image datasets in general and inspire further advances in the rapidly developing field of computational imaging.展开更多
基金supported by the National Natural Science Foundation of China (grant no.62305083 to W.Z.,grant no.T2222009 to H.L.,grant no.32227802 to H.L.)China Postdoctoral Science Foundation (grant no.2023T160163 to W.Z.grant no.2022M720971 to W.Z.)+2 种基金the Heilongjiang Provincial Postdoctoral Science Foundation (grant no.LBH-Z22027 to W.Z.)the National Key Research and Development Program of China (grant no.2022YFC3400600 to H.L.)the Natural Science Foundation of Heilongjiang Province (grant no.YQ2021F013 to H.L.).
文摘A critical function of flow cytometry is to count the concentration of blood cells,which helps in the diagnosis of certain diseases.However,the bulky nature of commercial flow cytometers makes such tests only available in hospitals or laboratories,hindering the spread of point-of-care testing(POCT),especially in underdeveloped areas.Here,we propose a smart Palm-size Optofluidic Hematology Analyzer based on a miniature fluorescence microscope and a microfluidic platform to lighten the device to improve its portability.This gadget has a dimension of 35×30×80 mm and a mass of 39 g,less than 5%of the weight of commercially available flow cytometers.Additionally,automatic leukocyte concentration detection has been realized through the integration of image processing and leukocyte counting algorithms.We compared the leukocyte concentration measurement between our approach and a hemocytometer using the Passing-Bablok analysis and achieved a correlation coefficient of 0.979.Through Bland-Altman analysis,we obtained the relationship between their differences and mean measurement values and established 95%limits of agreement,ranging from−0.93×10^(3)to 0.94×10^(3)cells/μL.We anticipate that this device can be used widely for monitoring and treating diseases such as HIV and tumors beyond hospitals.
基金supported by the National Natural Science Foundation of China(grant no.T2222009 to H.L.,grant no.32227802 to L.C.,grant no.81925022 to L.C.,grant no.92054301 to L.C.,grant no.62305083 to W.Z.,grant no.12174208 to P.L.,grant no.32301257 to S.Z.,grant no.32222022 to Y.J.,grant no.32071458 to H.M.)the National Key Research and Development Program of China(grant no.2022YFC3400600 to L.C.)+4 种基金the Natural Science Foundation of Heilongjiang Province(grant no.YQ2021F013 to H.L.)the Beijing Natural Science Foundation(grant no.Z20J00059 to L.C.)the Guangdong Major Project of Basic and Applied Basic Research(grant no.2020B0301030009 to P.L.)the China Postdoctoral Science Foundation(grant no.2023T160163 to W.Z.,grant no.2022M720971 to W.Z.)the Heilongjiang Provincial Postdoctoral Science Foundation(grant no.LBH-Z22027 to W.Z.).L.C.acknowledges support from the High-performance Computing Platform of Peking University。
文摘In fluorescence microscopy,computational algorithms have been developed to suppress noise,enhance contrast,and even enable super-resolution(SR).However,the local quality of the images may vary on multiple scales,and these differences can lead to misconceptions.Current mapping methods fail to finely estimate the local quality,challenging to associate the SR scale content.Here,we develop a rolling Fourier ring correlation(rFRC)method to evaluate the reconstruction uncertainties down to SR scale.To visually pinpoint regions with low reliability,a filtered rFRC is combined with a modified resolution-scaled error map(RSM),offering a comprehensive and concise map for further examination.We demonstrate their performances on various SR imaging modalities,and the resulting quantitative maps enable better SR images integrated from different reconstructions.Overall,we expect that our framework can become a routinely used tool for biologists in assessing their image datasets in general and inspire further advances in the rapidly developing field of computational imaging.
