The presence of micronucleus in human lymphocyte is an indicator of an un-healthy living environment. As a consequence, their counting allows to detect possible hazard for human health. The main problem is that the counting performed manually by experts on images acquired under the microscope, makes this measurement expensive, time consuming, and depending on the ability of the expert. A promising solution to overcome these problems has been the introduction of programs for automatic image analysis. However, also this method can lead to an erroneous interpretation of the data due to the image alterations produced by the acquisition system. This paper proposes an alternative system to identify and correct automatically some of the main alterations which can affect images acquired by the imaging flow cytometry, such as (i) underexposure, (ii) overexposure, (iii) blur, (iv) Gaussian noise. The aim of this study is to make each acquired image able to be rightly processed by the pattern matching algorithm used to detect the micronucleus and to reduce the unsure detections. The numerical outcomes prove the validity of the proposed correction method.

Living Environment Quality Monitoring: Image pre- processing to improve the human lymphocyte micronucleus detection

Lamonaca F.;
2022

Abstract

The presence of micronucleus in human lymphocyte is an indicator of an un-healthy living environment. As a consequence, their counting allows to detect possible hazard for human health. The main problem is that the counting performed manually by experts on images acquired under the microscope, makes this measurement expensive, time consuming, and depending on the ability of the expert. A promising solution to overcome these problems has been the introduction of programs for automatic image analysis. However, also this method can lead to an erroneous interpretation of the data due to the image alterations produced by the acquisition system. This paper proposes an alternative system to identify and correct automatically some of the main alterations which can affect images acquired by the imaging flow cytometry, such as (i) underexposure, (ii) overexposure, (iii) blur, (iv) Gaussian noise. The aim of this study is to make each acquired image able to be rightly processed by the pattern matching algorithm used to detect the micronucleus and to reduce the unsure detections. The numerical outcomes prove the validity of the proposed correction method.
978-1-6654-0893-6
Gaussian noise
image quality
imaging flow cytometer
out of focus
over-exposure
pattern matching
under-exposure
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/338447
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