Perception Thresholding for Noise Removal in Micrographs of Cellular Tissues Acquired by Fluorescence Microscopy

2018 ◽  
Author(s):  
Saad Manzur ◽  
Md. Badiul Haque Shawon ◽  
Mahmuda Naznin ◽  
Tanvir R. Faisal
Keyword(s):  
Spatial Modeling ◽  
Woody Plant ◽  
Similarity Index ◽  
Hierarchical Structures ◽  
Noise Removal ◽  
Cellular Tissue ◽  
Experimental Procedure ◽  
Local Thresholding ◽  
Otsu’S Method ◽  
A Cell

Plant petioles and stems are hierarchical structures comprising cellular tissues in one or more intermediate hierarchies displaying quasi random to heterogeneous cellularity that governs the overall structural properties. Exact replication of natural cellular tissue leads to the investigation of mechanical properties at the microstructural level. However, the micrographs often display artifacts due to experimental procedure and prevent representative spatial modeling of the tissues. Existing methods such as local thresholding or global thresholding (Otsu’s method) fail to effectively remove the artifacts. Hence, an efficient algorithm is required that can effectively help to reconstruct the geometric models of tissue microstructures by removing the noise. In this work, perception-based thresholding that conceptually works like human brain in differentiating noise from the actual ones based on color is introduced to remove discrete (within a cell) or adjacent (to the cell boundaries) noise. A variety of image dataset of non-woody plant tissues were tested with the algorithm, and its effectiveness in eliminating noise was quantitatively compared with existing noise removal techniques by Bivariate Similarity Index. The bivariate metrics indicate an enhanced performance of the perception-based thresholding over other considered algorithms.

scholarly journals Laplacian Eigenmaps Network-Based Nonlocal Means Method for MR Image Denoising

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2918 ◽  
Author(s):  
Houqiang Yu ◽  
Mingyue Ding ◽  
Xuming Zhang
Keyword(s):  
Similarity Index ◽  
Similarity Measures ◽  
Noise Removal ◽  
Human Vision ◽  
Rician Noise ◽  
Mr Images ◽  
Laplacian Eigenmaps ◽  
Nonlocal Means ◽  
Output Layer ◽  
Denoised Image

Magnetic resonance (MR) images are often corrupted by Rician noise which degrades the accuracy of image-based diagnosis tasks. The nonlocal means (NLM) method is a representative filter in denoising MR images due to its competitive denoising performance. However, the existing NLM methods usually exploit the gray-level information or hand-crafted features to evaluate the similarity between image patches, which is disadvantageous for preserving the image details while smoothing out noise. In this paper, an improved nonlocal means method is proposed for removing Rician noise in MR images by using the refined similarity measures. The proposed method firstly extracts the intrinsic features from the pre-denoised image using a shallow convolutional neural network named Laplacian eigenmaps network (LEPNet). Then, the extracted features are used for computing the similarity in the NLM method to produce the denoised image. Finally, the method noise of the denoised image is utilized to further improve the denoising performance. Specifically, the LEPNet model is composed of two cascaded convolutional layers and a nonlinear output layer, in which the Laplacian eigenmaps are employed to learn the filter bank in the convolutional layers and the Leaky Rectified Linear Unit activation function is used in the final output layer to output the nonlinear features. Due to the advantage of LEPNet in recovering the geometric structure of the manifold in the low-dimension space, the features extracted by this network can facilitate characterizing the self-similarity better than the existing NLM methods. Experiments have been performed on the BrainWeb phantom and the real images. Experimental results demonstrate that among several compared denoising methods, the proposed method can provide more effective noise removal and better details preservation in terms of human vision and such objective indexes as peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM).

Adaptive Trimmed Median Filter for Impulse Noise Detection and Removal with an Application to Mammogram Images

2020 ◽  
Vol 20 (04) ◽  
pp. 2050032
Author(s):  
Rubul Kumar Bania ◽  
Anindya Halder
Keyword(s):  
Breast Cancer ◽  
Impulse Noise ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Statistical Significance ◽  
Similarity Index ◽  
Structural Similarity ◽  
Noise Removal ◽  
Quantitative Indices ◽  
Mammogram Images

Mammography imaging is one of the most widely used techniques for breast cancer screening and analysis of abnormalities. However, due to some technical difficulties during the time of acquisition and digital storage of mammogram images, impulse noise may be present. Therefore, detection and removals of impulse noise from the mammogram images are very essential for early detection and further diagnosis of breast cancer. In this paper, a novel adaptive trimmed median filter (ATMF) is proposed for impulse noise (salt & pepper (SNP)) detection and removal with an application to mammogram image denoising. Automatic switching mechanism for updating the Window of Interest (WoI) size from ([Formula: see text]) to ([Formula: see text]) or ([Formula: see text]) is performed. The proposed method is applied on publicly available mammogram images corrupted with varying SNP noise densities in the range 5%–90%. The performance of the proposed method is measured by various quantitative indices like peak signal to noise ratio (PSNR), mean square error (MSE), image enhancement factor (IEF) and structural similarity index measure (SSIM). The comparative analysis of the proposed method is done with respect to other state-of-the-art noise removal methods viz., standard median filter (SMF), decision based median filter (DMF), decision based unsymmetric trimmed median filter (DUTMF), modified decision based unsymmetric trimmed median filter (MDUTMF) and decision based unsymmetric trimmed winsorized mean filter (DUTWMF). The superiority of the proposed method over other compared methods is well evident from the experimental results in terms of the quantitative indices (viz., PSNR, IEF and SSIM) and also from the visual quality of the denoised images. Paired t-test confirms the statistical significance of the higher PSNR values achieved by the proposed method as compared to the other counterpart techniques. The proposed method turned out to be very effective in denoising both high and low density noises present in (mammogram) images.

scholarly journals Brain Tissue Evaluation Based on Skeleton Shape and Similarity Analysis between Hemispheres

Computation ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 31
Author(s):  
Lenuta Pana ◽  
Simona Moldovanu ◽  
Nilanjan Dey ◽  
Amira S. Ashour ◽  
Luminita Moraru
Keyword(s):  
Brain Tissue ◽  
Right Hemisphere ◽  
Similarity Index ◽  
Region Of Interest ◽  
Structural Similarity ◽  
Noise Removal ◽  
Mirror Reflection ◽  
Proton Density ◽  
Rician Noise ◽  
Evaluation Tool

Background: The purpose of this article is to provide a new evaluation tool based on skeleton maps to assess the tumoral and non-tumoral regions of the 2D MRI in PD-weighted (proton density) and T2w (T2-weighted type) brain images. Methods: The proposed method investigated inter-hemisphere brain tissue similarity using a mask in the right hemisphere and its mirror reflection in the left one. At the hemisphere level and for each ROI (region of interest), a morphological skeleton algorithm was used to efficiently investigate the similarity between hemispheres. Two datasets with 88 T2w and PD images belonging to healthy patients and patients diagnosed with glioma were investigated: D1 contains the original raw images affected by Rician noise and D2 consists of the same images pre-processed for noise removal. Results: The investigation was based on structural similarity assessment by using the Structural Similarity Index (SSIM) and a modified Jaccard metrics. A novel S-Jaccard (Skeleton Jaccard) metric was proposed. Cluster accuracy was estimated based on the Silhouette method (SV). The Silhouette coefficient (SC) indicates the quality of the clustering process for the SSIM and S-Jaccard. To assess the overall classification accuracy an ROC curve implementation was carried out. Conclusions: Consistent results were obtained for healthy patients and for PD images of glioma. We demonstrated that the S-Jaccard metric based on skeletal similarity is an efficient tool for an inter-hemisphere brain similarity evaluation. The accuracy of the proposed skeletonization method was smaller for the original images affected by Rician noise (AUC = 0.883 (T2w) and 0.904 (PD)) but increased for denoised images (AUC = 0.951 (T2w) and 0.969 (PD)).

Thresholding Techniques for Dental Radiographic Images

2019 ◽  
pp. 40-61
Author(s):  
Arockia Sukanya ◽  
Kamalanand Krishnamurthy
Keyword(s):  
Early Detection ◽  
Imaging Techniques ◽  
Accurate Diagnosis ◽  
Diagnostic Process ◽  
Radiographic Images ◽  
Fundamental Step ◽  
Local Thresholding ◽  
Otsu’S Method ◽  
Global Thresholding ◽  
Natural Way

Imaging techniques play a major role in improving the early detection and diagnostic process that helps dentists to make accurate diagnosis. One of the most useful medical images used by dentists is radiographic image, which is used for the treatment of various dental disorders. Segmentation is a fundamental step as it involves separation of an image into regions corresponding to the objects. A simple and natural way to segment such regions is through thresholding. In this chapter, various thresholding techniques such as Otsu's method for global thresholding and Niblack's, Bersen's, and Sauvola's techniques for local thresholding are extensively explained with the help of dental radiographic images.

Periodic noise removal using local thresholding

2016 ◽  
Author(s):  
Vipin Prakash Yadav ◽  
Gajendra Singh ◽  
Md. Imtiyaz Anwar ◽  
Arun Khosla
Keyword(s):  
Noise Removal ◽  
Periodic Noise ◽  
Local Thresholding

scholarly journals Diet and sexual segregation of desert bighorn sheep (Ovis canadensis mexicana Merriam) in Sonora, Mexico

2021 ◽  
Author(s):  
Fernando Isaac Gastelum-Mendoza ◽  
Luis Antonio Tarango-Arámbula ◽  
Genaro Olmos-Oropeza ◽  
Jorge Palacio-Núñez ◽  
Diego Valdez-Zamudio ◽  
...  
Keyword(s):  
Diversity Index ◽  
Similarity Index ◽  
Food Preferences ◽  
Bighorn Sheep ◽  
Ovis Canadensis ◽  
Sexual Segregation ◽  
Desert Bighorn Sheep ◽  
Fecal Samples ◽  
A Cell ◽  
Species Being

Objective: To determine the diet of the desert bighorn sheep and to identify differencesin its composition between sexes during the reproductive and sexual segregation periods.Design/methodology/approach: The study was carried in the UMA Rancho NocheBuena, Hermosillo, Sonora. The microhistological technique and a cell catalog of plantsfrom the study area were used to identify plant species present in fecal samples ofbighorn sheep. The relative frequency, the Shannon-Weaver diversity index and theKulczynski similarity index were determined by sex and period (reproductive andsegregation)Results: The diet of bighorn sheep included 40 species, being herbaceous (36.1 ±4.4%) and grasses (26.8 ±8.9 %) the most common. The diet of males during thesegregation period was mainly composed of grasses (36.2%) and female diet byherbaceous (30%) and grasses (29.8%). No differences were found in the diversity ofthe diet of males and females in the segregation period (H '= 1.0) and in general, their diets were very similar (80%).Limitations/implications: To collect a greater number of fecal samples by sex andperiod (reproductive and segregation) and to analyze the nutritional content of plantsconsumed by bighorn sheep.Findings/conclusions: In this study, the sexual segregation exhibited by the bighornsheep in the Wildlife Management and Conservation Unit Rancho Noche Buena was notdue to food preferences.

Discrete Total Variation-Based Non-Local Means Filter for Denoising Magnetic Resonance Images

2020 ◽  
Vol 13 (4) ◽  
pp. 14-31
Author(s):  
Nikita Joshi ◽  
Sarika Jain ◽  
Amit Agarwal
Keyword(s):  
Magnetic Resonance ◽  
Total Variation ◽  
Similarity Index ◽  
Noise Removal ◽  
Magnetic Resonance Images ◽  
Variation Method ◽  
Mr Images ◽  
Denoising Method ◽  
Local Means ◽  
Non Local

Magnetic resonance (MR) images suffer from noise introduced by various sources. Due to this noise, diagnosis remains inaccurate. Thus, removal of noise becomes a very important task when dealing with MR images. In this paper, a denoising method has been discussed that makes use of non-local means filter and discrete total variation method. The proposed approach has been compared with other noise removal techniques like non-local means filter, anisotropic diffusion, total variation, and discrete total variation method, and it proves to be effective in reducing noise. The performance of various denoising methods is compared on basis of metrics such as peak signal-to-noise ratio (PSNR), mean square error (MSE), universal image quality index (UQI), and structure similarity index (SSIM) values. This method has been tested for various noise levels, and it outperformed other existing noise removal techniques, without blurring the image.

scholarly journals Enhanced activation of cellular AMPK by dual-small molecule treatment: AICAR and A769662

2014 ◽  
Vol 306 (6) ◽  
pp. E688-E696 ◽  
Author(s):  
Serge Ducommun ◽  
Rebecca J. Ford ◽  
Laurent Bultot ◽  
Maria Deak ◽  
Luc Bertrand ◽  
...  
Keyword(s):  
Synergistic Effect ◽  
Metabolic Diseases ◽  
Cellular Tissue ◽  
Intact Cells ◽  
Downstream Signaling ◽  
Upstream Kinase ◽  
A Cell ◽  
Single Compound ◽  
Ampk Activity ◽  
Amp Activated Protein Kinase

AMP-activated protein kinase (AMPK) is a key cellular energy sensor and regulator of metabolic homeostasis. Activation of AMPK provides beneficial outcomes in fighting against metabolic disorders such as insulin resistance and type 2 diabetes. Currently, there is no allosteric AMPK activator available for the treatment of metabolic diseases, and limited compounds are available to robustly stimulate cellular/tissue AMPK in a specific manner. Here we investigated whether simultaneous administration of two different pharmacological AMPK activators, which bind and act on different sites, would result in an additive or synergistic effect on AMPK and its downstream signaling and physiological events in intact cells. We observed that cotreating primary hepatocytes with the AMP mimetic 5-aminoimidazole-4-carboxamide-1-β-d-ribofuranoside (AICAR) and a low dose (1 μM) of the allosteric activator A769662 produced a synergistic effect on AMPK Thr172 phosphorylation and catalytic activity, which was associated with a more profound increase/decrease in phosphorylation of downstream AMPK targets and inhibition of hepatic lipogenesis compared with single-compound treatment. Mechanistically, we found that cotreatment does not stimulate LKB1, upstream kinase for AMPK, but it protects against dephosphorylation of Thr172 phosphorylation by protein phosphatase PP2Cα in an additive manner in a cell-free assay. Collectively, we demonstrate that AICAR sensitizes the effect of A769662 and promotes AMPK activity and its downstream events. The study demonstrates the feasibility of promoting AMPK activity by using two activators with distinct modes of action in order to achieve a greater activation of AMPK and downstream signaling.

Elicitor-induced defence responses of a suspension-cultured woody plant (Larix decidua) and possible mechanisms of signal transduction

1997 ◽  
Vol 75 (8) ◽  
pp. 1243-1251 ◽  
Author(s):  
Martina Bach ◽  
Hanns Ulrich Seitz
Keyword(s):  
Signal Transduction ◽  
Fusarium Oxysporum ◽  
Woody Plant ◽  
Inositol Phosphates ◽  
Calcium Influx ◽  
Lignin Biosynthesis ◽  
Larix Decidua ◽  
Rapid Responses ◽  
A Cell ◽  
Defence Responses

Treatment of suspension-cultured larch cells (Larix decidua Mill.) with an elicitor derived from the cell wall of Fusarium oxysporum Schlecht. triggers very rapid defence responses like an oxidative burst and an increased calcium influx from the medium into the cell, all occurring within minutes after elicitation. These rapid responses are followed by a much slower set of changes like increased activities of phenylalanine ammonia-lyase and peroxidases and enhanced lignin biosynthesis. This paper describes both rapid and slow reactions of a cell culture derived from a woody plant to an elicitor from a facultative pathogen. Experiments concerning the transduction of the elicitor signal showed that the presence of calcium in the medium is indispensable for all elicitor responses of larch cells. It can be demonstrated that H2O2 is not a part of the signal chain. The importance of inositol phosphates and protein phosphorylation were studied using inhibitors. Neomycin, an inhibitor of the phosphoinositol pathway, blocked only the slower responses whereas staurosporine, an inhibitor of protein kinases, blocked both rapid and all the slower reactions. These results support the hypothesis that phosphorylation plays an important role even in very early stages of the signal transduction. Key words: elicitor, Fusarium oxysporum, H2O2, Larix decidua, lignin.

scholarly journals Micropatterning Method for Porous Materials Using the Difference of the Glass Transition Temperature between Exposed and Unexposed Areas of a Thick-Photoresist

Micromachines ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 54
Author(s):  
Hidetaka Ueno ◽  
Kiichi Sato ◽  
Kou Yamada ◽  
Takaaki Suzuki
Keyword(s):  
Glass Transition ◽  
Transition Temperature ◽  
Glass Transition Temperature ◽  
Porous Material ◽  
3D Structure ◽  
Porous Membrane ◽  
Cellular Tissue ◽  
A Cell ◽  
Thick Photoresist ◽  
The Difference

A cell culture on a scaffold has the advantages of functionality and easy handling, because the geometry of the cellular tissue is controlled by designing the scaffold. To create complex cellular tissue, scaffolds should be complex two-dimensional (2D) and three-dimensional (3D) structures. However, it is difficult to fabricate a scaffold with a 2D and 3D structure because the shape, size, and fabrication processes of a 2D structure in creating a cell layer, and a 3D structure containing cells, are different. In this research, we propose a micropatterning method for porous materials using the difference of the glass transition temperature between exposed and unexposed areas of a thick-photoresist. Since the proposed method does not require a vacuum, high temperature, or high voltage, it can be used for fabricating various structures with a wide range of scales, regardless of the materials used. Additionally, the patterning area can be fabricated accurately by photolithography. To evaluate the proposed method, a membrane integrated scaffold (MIS) with a 2D porous membrane and 3D porous material was fabricated. The MIS had a porous membrane with a pore size of 4 μm or less, which was impermeable to cells, and a porous material which was capable of containing cells. By seeding HUVECs and HeLa cells on each side of the MIS, the cellular tissue was formed with the designed geometry.

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