Quan Zhenhua, Xu Shilin, Liao Xiaobo, Wu Bin, Luo Liang
School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China.
Sensors (Basel). 2024 May 22;24(11):3291. doi: 10.3390/s24113291.
Scanning ion conductance microscopy (SICM) enables the non-invasive three-dimensional imaging of live cells and other structures in physiological environments. However, when imaging complex samples, SICM faces challenges such as having a low temporal resolution during slow scanning and a reduced signal-to-noise ratio during fast scanning, making it difficult to simultaneously improve both temporal and spatial resolution. To address these issues, this paper proposes an algorithm for enhancing image resolution under high-speed scanning. Firstly, scanning images are preprocessed using a median filtering algorithm to remove the salt-and-pepper noise generated during high-speed scanning. Next, the Canny edge detection algorithm is employed to extract the edges of the image targets. To avoid blurring the edges, the new edge-directed interpolation (NEDI) algorithm is then used to fill the edges, while non-edge areas are filled using bilinear interpolation, thereby enhancing the image resolution. Finally, the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) are used to analyze the imaging of articular chondrocytes. The results show that under a scanning speed of 480 nm/ms, the proposed algorithm improves the temporal resolution of imaging by 60% compared to traditional 2× resolution imaging, increases the peak signal-to-noise ratio of the scanning images by 7 dB, and achieves a structural similarity of 0.97. Therefore, the proposed algorithm effectively removes noise during high-speed scanning and improves the SICM scanning imaging resolution, thereby avoiding the reduction in temporal resolution when scanning larger resolution samples and effectively enhancing the performance of SICM scanning imaging.
扫描离子电导显微镜（SICM）能够对生理环境中的活细胞和其他结构进行非侵入性三维成像。然而，在对复杂样本进行成像时，SICM面临着诸如慢扫描时时间分辨率低以及快扫描时信噪比降低等挑战，这使得难以同时提高时间和空间分辨率。为了解决这些问题，本文提出了一种用于在高速扫描下提高图像分辨率的算法。首先，使用中值滤波算法对扫描图像进行预处理，以去除高速扫描过程中产生的椒盐噪声。接下来，采用Canny边缘检测算法提取图像目标的边缘。为避免边缘模糊，随后使用新的边缘导向插值（NEDI）算法填充边缘，而非边缘区域则使用双线性插值进行填充，从而提高图像分辨率。最后，使用峰值信噪比（PSNR）和结构相似性指数（SSIM）来分析关节软骨细胞的成像。结果表明，在480 nm/ms的扫描速度下，与传统的2倍分辨率成像相比，所提出的算法将成像的时间分辨率提高了60%，扫描图像的峰值信噪比提高了7 dB，并且实现了0.97的结构相似性。因此，所提出的算法有效地去除了高速扫描过程中的噪声，提高了SICM扫描成像分辨率，从而避免了在扫描更大分辨率样本时时间分辨率的降低，并有效地提高了SICM扫描成像的性能。
