Fast Multi-Focus Fusion Based on Deep Learning for Early-Stage Embryo Image Enhancement

Abstract

Background: Cell detection and counting is of essential importance in evaluating the quality of early-stage embryo. Full automation of this process remains a challenging task due to different cell size, shape, the presence of incomplete cell boundaries, partially or fully overlapping cells. Moreover, the algorithm to be developed should process a large number of image data of different quality in a reasonable amount of time. Methods: Multi-focus image fusion approach based on deep learning U-Net architecture is proposed in the paper, which allows reducing the amount of data up to 7 times without losing spectral information required for embryo enhancement in the microscopic image. Results: The experiment includes the visual and quantitative analysis by estimating the image similarity metrics and processing times, which is compared to the results achieved by two wellknown techniques—Inverse Laplacian Pyramid Transform and Enhanced Correlation Coefficient Maximization. Conclusion: Comparatively, the image fusion time is substantially improved for different image resolutions, whilst ensuring the high quality of the fused image.

Segmentation of Drilled Holes in Texture Wooden Furniture Panels Using Deep Neural Network

“…The proposed neural network model or modifications can be engaged in problems such as remote image segmentation [ 65 , 66 ], medicine [ 67 , 68 ], faults detection [ 69 , 70 ], and others.…”

Illumination-aware image fusion for around-the-clock human detection in adverse environments from Unmanned Aerial Vehicle

“…An optimised Enhanced Correlation Coefficient (ECC) method (Evangelidis and Psarakis, 2008), was designed due to being highly effective and fast for registration of heterogeneous images. ECC is a gradient-based image registration algorithm invariant to global illumination changes (Raudonis et al, 2021;Choi et al, 2017;López et al, 2021;Hwooi and Sabri, 2017). The ECC algorithm was optimised in terms of iterations and precision factor to fulfil the requirements of the use case.…”