A Fusion Method for Atomic Force Acoustic Microscopy Cell Imaging Based on Local Variance in Non-Subsampled Shearlet Transform Domain

Pengxin Cao,Mingyue Ding,Xiaoqing Li

doi:10.3390/app10217424

Abstract

Atomic force acoustic microscopy (AFAM) is a measurement method that uses the probe and acoustic wave to image the surface and internal structures of different materials. For cellular material, the morphology and phase images of AFAM reflect the outer surface and internal structures of the cell, respectively. This paper proposes an AFAM cell image fusion method in the Non-Subsampled Shearlet Transform (NSST) domain, based on local variance. First, NSST is used to decompose the source images into low-frequency and high-frequency sub-bands. Then, the low-frequency sub-band is fused by the weight of local variance, while a contrast limited adaptive histogram equalization is used to improve the source image contrast to better express the details in the fused image. The high-frequency sub-bands are fused using the maximum rule. Since the AFAM image background contains a lot of noise, and improved segmentation algorithm based on the Otsu algorithm is proposed to segment the cell region, and the image quality metrics based on the segmented region will make the evaluation more accurate. Experiments with different groups of AFAM cell images demonstrated that the proposed method can clearly show the internal structures and the contours of the cells, compared with traditional methods.

Highlights

Atomic force acoustic microscopy (AFAM) [1] is an imaging technology combining acoustic detection and atomic force microscopy (AFM), which can image nondestructively the internal structures, as well as the surface topography of the samples in high resolution
Sixteen groups of morphology and phase images were used from 2 scans in Ref. [1] for testing, which were provided by the Medical Ultrasonic Laboratory of Huazhong University of Science and Technology, Wuhan, China
Our fusion method is compared with five different fusion methods, including Laplacian pyramid (LP) [17], curvelet transform (CVT) [18], Non-Subsampled Shearlet Transform (NSST)-VGG [19], gradient transfer fusion (GFT) [20], and FusionGAN [21]

Summary

Introduction

Atomic force acoustic microscopy (AFAM) [1] is an imaging technology combining acoustic detection and atomic force microscopy (AFM), which can image nondestructively the internal structures, as well as the surface topography of the samples in high resolution. The morphology and phase images were obtained simultaneously after the scanning of the sample in 2D. When AFAM is applied to image cells, the morphology images could only show cytoplasmic regions, while their phase images showed the cytoplasmic internal structures, but without the cell boundaries clearly [1]. To see the cells in detail, image fusion is needed to fuse both images so that the fused image can contain both information of the morphology contour and the internal structures of the cell. There is no such research on AFAM image fusion yet

Methods

Results

Conclusion