PURE-LET Deconvolution of 3D Fluorescence Microscopy Images
Refereed conference paper presented and published in conference proceedings

替代計量分析
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其它資訊
摘要Three-dimensional (3D) deconvolution microscopy is very effective in improving the quality of fluorescence microscopy images. In this work, we present an efficient approach for the deconvolution of 3D fluorescence microscopy images based on the recently developed PURE-LET algorithm. By combining multiple Wiener filtering and wavelet denoising, we parametrize the deconvolution process as a linear combination of elementary functions. Then the Poisson unbiased risk estimate (PURE) is used to obtain the optimal coefficients. The proposed approach is non-iterative and outperforms existing techniques (usually, variants of Richardson-Lucy algorithm) both in terms of computational efficiency and quality. We illustrate its effectiveness on both synthetic and real data.
著者Li J., Luisier F., Blu T
會議名稱Fourteenth IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI'17)
會議開始日18.04.2017
會議完結日21.04.2017
會議地點Melbourne
會議國家/地區澳大利亞
會議論文集題名Biomedical Imaging (ISBI 2017), 2017 IEEE 14th International Symposium on
出版年份2017
出版社IEEE
頁次723 - 727
國際標準書號978-1-5090-1173-5
電子國際標準書號978-1-5090-1172-8
電子國際標準期刊號1945-8452
語言美式英語

上次更新時間 2020-20-11 於 00:38