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公开(公告)号:US08135187B2
公开(公告)日:2012-03-13
申请号:US12056078
申请日:2008-03-26
申请人: Ali Can , Michael John Gerdes , Musodiq Olatayo Bello , Xiaodong Tao , Francis Edward Pavan-Woolfe , Roshni Bhagalia
发明人: Ali Can , Michael John Gerdes , Musodiq Olatayo Bello , Xiaodong Tao , Francis Edward Pavan-Woolfe , Roshni Bhagalia
CPC分类号: G06K9/0014 , G01N21/6458
摘要: Techniques for removing image autoflourescence from fluorescently stained biological images are provided herein. The techniques utilize non-negative matrix factorization that may constrain mixing coefficients to be non-negative. The probability of convergence to local minima is reduced by using smoothness constraints. The non-negative matrix factorization algorithm provides the advantage of removing both dark current and autofluorescence.
摘要翻译: 本文提供了从荧光染色的生物图像中去除图像自动曝光的技术。 这些技术利用可以将混合系数限制为非负的非负矩阵分解。 通过使用平滑度约束来减少收敛到局部最小值的概率。 非负矩阵分解算法提供了去除暗电流和自发荧光的优点。
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公开(公告)号:US20090245611A1
公开(公告)日:2009-10-01
申请号:US12056078
申请日:2008-03-26
申请人: Ali Can , Michael John Gerdes , Musodiq Olatayo Bello , Xiaodong Tao , Francis Edward Pavan-Woolfe , Roshni Bhagalia
发明人: Ali Can , Michael John Gerdes , Musodiq Olatayo Bello , Xiaodong Tao , Francis Edward Pavan-Woolfe , Roshni Bhagalia
IPC分类号: G06K9/00
CPC分类号: G06K9/0014 , G01N21/6458
摘要: Techniques for removing image autoflourescence from fluorescently stained biological images are provided herein. The techniques utilize non-negative matrix factorization that may constrain mixing coefficients to be non-negative. The probability of convergence to local minima is reduced by using smoothness constraints. The non-negative matrix factorization algorithm provides the advantage of removing both dark current and autofluorescence.
摘要翻译: 本文提供了从荧光染色的生物图像中去除图像自动曝光的技术。 这些技术利用可以将混合系数限制为非负的非负矩阵分解。 通过使用平滑度约束来减少收敛到局部最小值的概率。 非负矩阵分解算法提供了去除暗电流和自发荧光的优点。
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