Marine self-potential gradient exploration of the continental margin

Geophysics ◽  
2005 ◽  
Vol 70 (5) ◽  
pp. G109-G118 ◽  
Author(s):  
Graham Heinson ◽  
Antony White ◽  
David Robinson ◽  
Nader Fathianpour
Keyword(s):  
Mineral Exploration ◽  
South Australia ◽  
Potential Gradient ◽  
Ocean Waves ◽  
Horizontal Gradient ◽  
Reconstruction Method ◽  
Source Regions ◽  
Image Reconstruction Method ◽  
Numerical Finite Element ◽  
Self Potential

The self-potential (SP) method for mineral exploration is seldom used on land, primarily because of electrode noise problems and nonunique interpretations. Marine measurements of the horizontal gradient of the SP field, on the other hand, are relatively simple to make with an array of electrodes towed behind a ship. With low ship speeds of 5 to 10 km/hour, dense spatial sampling (∼1 m) can be obtained with resolution of better than 1 μV/m. In this paper we report on gradient SP data recorded on the continental shelf of South Australia by a horizontal array of towed electrodes approximately 20 m above the seafloor. Ocean waves and swells with periods of 5 to 15 s yielded large amplitude signals ±20 μV/m, but subseafloor mineralization produced SP gradient anomalies of ±50 μV/m and widths of 2 km or more in a number of parallel traverses. Integrating the observed SP gradients along each line delineated SP anomalies of amplitude up to −100 mV. Self-potential and magnetic anomaly data show limited spatial correlation and have different wavelengths, suggesting that SP sources are probably nonferrous minerals, such as graphite, and are deeper than the magnetic sources. The source of the SP signal is probably reduction-oxidation (redox) potential ([Formula: see text]) variations across a conducting body below the seafloor. We approximate the source as being two dimensional and find the most probable locations of line sources by an image reconstruction method. Numerical finite-element modeling of more realistic source regions suggests shallow, easterly dipping (∼15°) conductors of 1 Ω.m in the uppermost 2 km.

Image Reconstruction with the Fourier Coefficients for Magnetic Induction Tomography

2020 ◽  
Vol 16 (2) ◽  
pp. 156-163
Author(s):  
Jingwen Wang ◽  
Xu Wang ◽  
Dan Yang ◽  
Kaiyang Wang
Keyword(s):  
Inverse Problem ◽  
Image Reconstruction ◽  
Magnetic Induction ◽  
Fourier Coefficients ◽  
Signal Reconstruction ◽  
Reconstruction Algorithm ◽  
Reconstruction Method ◽  
Measurement Equation ◽  
Image Reconstruction Method ◽  
Magnetic Induction Tomography

Background: Image reconstruction of magnetic induction tomography (MIT) is a typical ill-posed inverse problem, which means that the measurements are always far from enough. Thus, MIT image reconstruction results using conventional algorithms such as linear back projection and Landweber often suffer from limitations such as low resolution and blurred edges. Methods: In this paper, based on the recent finite rate of innovation (FRI) framework, a novel image reconstruction method with MIT system is presented. Results: This is achieved through modeling and sampling the MIT signals in FRI framework, resulting in a few new measurements, namely, fourier coefficients. Because each new measurement contains all the pixel position and conductivity information of the dense phase medium, the illposed inverse problem can be improved, by rebuilding the MIT measurement equation with the measurement voltage and the new measurements. Finally, a sparsity-based signal reconstruction algorithm is presented to reconstruct the original MIT image signal, by solving this new measurement equation. Conclusion: Experiments show that the proposed method has better indicators such as image error and correlation coefficient. Therefore, it is a kind of MIT image reconstruction method with high accuracy.

Automated Confluence Measurement Method for Mesenchymal Stem Cell from Brightfield Microscopic Images

2021 ◽  
pp. 1-9
Author(s):  
Zenan Wang ◽  
Rucai Zhan ◽  
Ying Hu
Keyword(s):  
Cell Culture ◽  
Phase Contrast ◽  
Low Cost ◽  
Cost Effective ◽  
Cell Phenotype ◽  
Cell Culture Process ◽  
Reconstruction Method ◽  
Image Reconstruction Method ◽  
Contrast Microscope ◽  
Culture Process

Cell confluence is an important metric in cell culture, as proper timing is essential to maintain cell phenotype and culture quality. To estimate cell confluence, transparent cells are observed under a phase-contrast or differential interference contrast microscope by a biologist, whose estimations are error-prone and subjective. To overcome the necessity of using the phase-contrast microscope and reducing intra- and inter-observer errors, we have proposed an algorithm that automatically measures cell confluence by using a commonly used brightfield microscope. The proposed method consists of a transport-of-intensity equation-based brightfield microscopic image processing, an image reconstruction method, and an adaptive image segmentation method based on edge detection, entropy filtering, and range filtering. Experimental results have shown that our method has outperformed several popular algorithms, with an F-score of 0.84 ± 0.07, in images with various cell confluence values. The proposed algorithm is robust and accurate enough to perform confluence measurement with various lighting conditions under a low-cost brightfield microscope, making it simple and cost-effective to use for a fully automated cell culture process.

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