Extended Data Fig. 3: Analysis of possible artifacts in the caveolae images reconstructed with the sparse deconvolution, which was further compared with other deconvolution methods. | Nature Biotechnology

Extended Data Fig. 3: Analysis of possible artifacts in the caveolae images reconstructed with the sparse deconvolution, which was further compared with other deconvolution methods.

From: Sparse deconvolution improves the resolution of live-cell super-resolution fluorescence microscopy

Extended Data Fig. 3

(a) A representative COS-7 cell labeled with caveolin-EGFP under TIRF-SIM and Sparse-SIM ×2 (whole FOV from Fig. 4j). (b-e) The region enclosed by the white box in (a) was magnified and shown under the non-iterative method (TIRF-SIM), sparse deconvolution (Sparse-SIM ×2), or sparse deconvolution followed by convolving back with the resolution scaled function (RSF). The RSF is estimated between TIRF-SIM and Sparse-SIM ×2, and the FWHM of this estimated RSF is 78 nm. (e) The resolution scaled error (RSE) map of Sparse-SIM ×2 against the raw TIRF-SIM image. Before the RSE map estimation, the intensity of TIRF-SIM and Sparse-SIM images are normalized to the range of 0~1, and the corresponding residual image (RSE map) is color-coded within the range of 0~1. (f) Magnified views in (b-e). (g) The region enclosed by the white rectangle in (f) was magnified and reconstructed with a non-iterative method (TIRF-SIM), followed by image squares (TIRF-SIM square), or Fourier interpolated followed by RL-deconvolution (TIRF-SIM + RL ×2) for 3 or 25 iterations, or Fourier interpolated followed by the sparse deconvolution (Sparse-SIM ×2). Experiments were repeated five times independently with similar results. Scale bars: (a-e) 2 μm; (f) 1 μm; (g) 100 nm.

Back to article page