Search results for: cellular images
2663 Reduction of the Cellular Infectivity of SARS-CoV-2 by a Mucoadhesive Nasal Spray
Authors: Adam M. Pitz, Gillian L. Phillipson, Jayant E. Khanolkar, Andrew M. Middleton
Abstract:
New emerging evidence suggests that the nose is the predominant route for entry of the SARS-CoV-2 virus into the host. A virucidal suspension test (conforming in principle to the European Standard EN14476) was conducted to determine whether a commercial liquid gel intranasal spray containing 1% of the mucoadhesive hydroxypropyl methylcellulose (HPMC) could inhibit the cellular infectivity of the SARS-CoV-2 coronavirus. Virus was added to the test product samples and to controls in a 1:8 ratio and mixed with one part bovine serum albumin as an interfering substance. The test samples were pre-equilibrated to 34 ± 2°C (representing the temperature of the nasopharynx) with the temperature maintained at 34 ± 2°C for virus contact times of 1, 5 and 10 minutes. Neutralized aliquots were inoculated onto host cells (Vero E6 cells, ATCC CRL-1586). The host cells were then incubated at 36 ± 2°C for a period of 7 days. The residual infectious virus in both test and controls was detected by viral-induced cytopathic effect. The 50% tissue culture infective dose per mL (TCID50/mL) was determined using the Spearman-Karber method with results reported as the reduction of the virus titer due to treatment with test product, expressed as log10. The controls confirmed the validity of the results with no cytotoxicity or viral interference observed in the neutralized test product samples. The HPMC formulation reduced SARS-CoV-2 titer, expressed as log10TCID50, by 2.30 ( ± 0.17), 2.60 ( ± 0.19), and 3.88 ( ± 0.19) with the respective contact times of 1, 5 and 10 minutes. The results demonstrate that this 1% HPMC gel formulation can reduce the cellular infectivity of the SARS-CoV-2 virus with an increasing viral inhibition observed with increasing exposure time. This 1% HMPC gel is well tolerated and can reside, when delivered via nasal spray, for up to one hour in the nasal cavity. We conclude that this intranasal gel spray with 1% HPMC repeat-dosed every few hours may offer an effective preventive or early intervention solution to limit the transmission and impact of the SARS-CoV-2 coronavirus.Keywords: hydroxypropyl methylcellulose, mucoadhesive nasal spray, respiratory viruses, SARS-CoV-2
Procedia PDF Downloads 1322662 Digital Development of Cultural Heritage: Construction of Traditional Chinese Pattern Database
Authors: Shaojian Li
Abstract:
The traditional Chinese patterns, as an integral part of Chinese culture, possess unique values in history, culture, and art. However, with the passage of time and societal changes, many of these traditional patterns are at risk of being lost, damaged, or forgotten. To undertake the digital preservation and protection of these traditional patterns, this paper will collect and organize images of traditional Chinese patterns. It will provide exhaustive and comprehensive semantic annotations, creating a resource library of traditional Chinese pattern images. This will support the digital preservation and application of traditional Chinese patterns.Keywords: digitization of cultural heritage, traditional Chinese patterns, digital humanities, database construction
Procedia PDF Downloads 552661 Resisting Adversarial Assaults: A Model-Agnostic Autoencoder Solution
Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone
Abstract:
The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder
Procedia PDF Downloads 1042660 Basic Study of Mammographic Image Magnification System with Eye-Detector and Simple EEG Scanner
Authors: Aika Umemuro, Mitsuru Sato, Mizuki Narita, Saya Hori, Saya Sakurai, Tomomi Nakayama, Ayano Nakazawa, Toshihiro Ogura
Abstract:
Mammography requires the detection of very small calcifications, and physicians search for microcalcifications by magnifying the images as they read them. The mouse is necessary to zoom in on the images, but this can be tiring and distracting when many images are read in a single day. Therefore, an image magnification system combining an eye-detector and a simple electroencephalograph (EEG) scanner was devised, and its operability was evaluated. Two experiments were conducted in this study: the measurement of eye-detection error using an eye-detector and the measurement of the time required for image magnification using a simple EEG scanner. Eye-detector validation showed that the mean distance of eye-detection error ranged from 0.64 cm to 2.17 cm, with an overall mean of 1.24 ± 0.81 cm for the observers. The results showed that the eye detection error was small enough for the magnified area of the mammographic image. The average time required for point magnification in the verification of the simple EEG scanner ranged from 5.85 to 16.73 seconds, and individual differences were observed. The reason for this may be that the size of the simple EEG scanner used was not adjustable, so it did not fit well for some subjects. The use of a simple EEG scanner with size adjustment would solve this problem. Therefore, the image magnification system using the eye-detector and the simple EEG scanner is useful.Keywords: EEG scanner, eye-detector, mammography, observers
Procedia PDF Downloads 2132659 View Synthesis of Kinetic Depth Imagery for 3D Security X-Ray Imaging
Authors: O. Abusaeeda, J. P. O. Evans, D. Downes
Abstract:
We demonstrate the synthesis of intermediary views within a sequence of X-ray images that exhibit depth from motion or kinetic depth effect in a visual display. Each synthetic image replaces the requirement for a linear X-ray detector array during the image acquisition process. Scale invariant feature transform, SIFT, in combination with epipolar morphing is employed to produce synthetic imagery. Comparison between synthetic and ground truth images is reported to quantify the performance of the approach. Our work is a key aspect in the development of a 3D imaging modality for the screening of luggage at airport checkpoints. This programme of research is in collaboration with the UK Home Office and the US Dept. of Homeland Security.Keywords: X-ray, kinetic depth, KDE, view synthesis
Procedia PDF Downloads 2572658 Detecting Manipulated Media Using Deep Capsule Network
Authors: Joseph Uzuazomaro Oju
Abstract:
The ease at which manipulated media can be created, and the increasing difficulty in identifying fake media makes it a great threat. Most of the applications used for the creation of these high-quality fake videos and images are built with deep learning. Hence, the use of deep learning in creating a detection mechanism cannot be overemphasized. Any successful fake media that is being detected before it reached the populace will save people from the self-doubt of either a content is genuine or fake and will ensure the credibility of videos and images. The methodology introduced in this paper approaches the manipulated media detection challenge using a combo of VGG-19 and a deep capsule network. In the case of videos, they are converted into frames, which, in turn, are resized and cropped to the face region. These preprocessed images/videos are fed to the VGG-19 network to extract the latent features. The extracted latent features are inputted into a deep capsule network enhanced with a 3D -convolution dynamic routing agreement. The 3D –convolution dynamic routing agreement algorithm helps to reduce the linkages between capsules networks. Thereby limiting the poor learning shortcoming of multiple capsule network layers. The resultant output from the deep capsule network will indicate a media to be either genuine or fake.Keywords: deep capsule network, dynamic routing, fake media detection, manipulated media
Procedia PDF Downloads 1232657 Estimating Leaf Area and Biomass of Wheat Using UAS Multispectral Remote Sensing
Authors: Jackson Parker Galvan, Wenxuan Guo
Abstract:
Unmanned aerial vehicle (UAV) technology is being increasingly adopted in high-throughput plant phenotyping for applications in plant breeding and precision agriculture. Winter wheat is an important cover crop for reducing soil erosion and protecting the environment in the Southern High Plains. Efficiently quantifying plant leaf area and biomass provides critical information for producers to practice site-specific management of crop inputs, such as water and fertilizers. The objective of this study was to estimate wheat biomass and leaf area index using UAV images. This study was conducted in an irrigated field in Garza County, Texas. High-resolution images were acquired on three dates (February 18, March 25, and May 15th ) using a multispectral sensor onboard a Matrice 600 UAV. On each data of image acquisition, 10 random plant samples were collected and measured for biomass and leaf area. Images were stitched using Pix4D, and ArcGIS was applied to overlay sampling locations and derive data for sampling locations.Keywords: precision agriculture, UAV plant phenotyping, biomass, leaf area index, winter wheat, southern high plains
Procedia PDF Downloads 912656 Depth Estimation in DNN Using Stereo Thermal Image Pairs
Authors: Ahmet Faruk Akyuz, Hasan Sakir Bilge
Abstract:
Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea.Keywords: thermal stereo matching, deep neural networks, CNN, Depth estimation
Procedia PDF Downloads 2672655 Speed up Vector Median Filtering by Quasi Euclidean Norm
Authors: Vinai K. Singh
Abstract:
For reducing impulsive noise without degrading image contours, median filtering is a powerful tool. In multiband images as for example colour images or vector fields obtained by optic flow computation, a vector median filter can be used. Vector median filters are defined on the basis of a suitable distance, the best performing distance being the Euclidean. Euclidean distance is evaluated by using the Euclidean norms which is quite demanding from the point of view of computation given that a square root is required. In this paper an optimal piece-wise linear approximation of the Euclidean norm is presented which is applied to vector median filtering.Keywords: euclidean norm, quasi euclidean norm, vector median filtering, applied mathematics
Procedia PDF Downloads 4622654 A Case Study of Deep Learning for Disease Detection in Crops
Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell
Abstract:
In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture
Procedia PDF Downloads 2472653 Communication About Health and Fitness in Media and Its Hidden Message About Objectification
Authors: Emiko Suzuki
Abstract:
Although fitness is defined as the body’s ability to respond to the demand of physical activity without undue fatigue in health science, in media oftentimes physical activity is presented as means to an attractive body rather than a fit and healthy one. Of all types of media, Instagram is becoming an increasingly persuasive source of information and advice on health and fitness, where individuals conceptualize what health and fitness mean for them. However, this user-generated and unregulated platform can be problematic, as it can communicate misleading information about health and fitness and possibly leading individuals to psychological problems such as eating disorders. In fact, previous research has shown that some messages that were posted with a tag that related to inspire others to do fitness, in fact, encouraged distancing the self from the internal needs of the body. For this reason, this present study aims to explore how health and fitness are communicated on Instagram by analyzing images and texts. A content analysis of images that were labeled with particular hashtags was performed, followed by a thematic analysis of texts from the same set of images. The result shows an interesting insight about messages about how health and fitness are communicated from companies through media, then digested and further shared among communities on Instagram. The study explores how the use of visual focused way of communicating health and fitness can lead to the dehumanization of human bodies.Keywords: Instagram, fitness, dehumanization, body image, embodiment
Procedia PDF Downloads 1332652 Image Enhancement of Histological Slides by Using Nonlinear Transfer Function
Authors: D. Suman, B. Nikitha, J. Sarvani, V. Archana
Abstract:
Histological slides provide clinical diagnostic information about the subjects from the ancient times. Even with the advent of high resolution imaging cameras the image tend to have some background noise which makes the analysis complex. A study of the histological slides is done by using a nonlinear transfer function based image enhancement method. The method processes the raw, color images acquired from the biological microscope, which, in general, is associated with background noise. The images usually appearing blurred does not convey the intended information. In this regard, an enhancement method is proposed and implemented on 50 histological slides of human tissue by using nonlinear transfer function method. The histological image is converted into HSV color image. The luminance value of the image is enhanced (V component) because change in the H and S components could change the color balance between HSV components. The HSV image is divided into smaller blocks for carrying out the dynamic range compression by using a linear transformation function. Each pixel in the block is enhanced based on the contrast of the center pixel and its neighborhood. After the processing the V component, the HSV image is transformed into a colour image. The study has shown improvement of the characteristics of the image so that the significant details of the histological images were improved.Keywords: HSV space, histology, enhancement, image
Procedia PDF Downloads 3262651 Evaluation of the Cytotoxicity and Cellular Uptake of a Cyclodextrin-Based Drug Delivery System for Cancer Therapy
Authors: Caroline Mendes, Mary McNamara, Orla Howe
Abstract:
Drug delivery systems are proposed for use in cancer treatment to specifically target cancer cells and deliver a therapeutic dose without affecting normal cells. For that purpose, the use of folate receptors (FR) can be considered a key strategy, since they are commonly over-expressed in cancer cells. In this study, cyclodextrins (CD) have being used as vehicles to target FR and deliver the chemotherapeutic drug, methotrexate (MTX). CDs have the ability to form inclusion complexes, in which molecules of suitable dimensions are included within their cavities. Here, β-CD has been modified using folic acid so as to specifically target the FR. Thus, this drug delivery system consists of β-CD, folic acid and MTX (CDEnFA:MTX). Cellular uptake of folic acid is mediated with high affinity by folate receptors while the cellular uptake of antifolates, such as MTX, is mediated with high affinity by the reduced folate carriers (RFCs). This study addresses the gene (mRNA) and protein expression levels of FRs and RFCs in the cancer cell lines CaCo-2, SKOV-3, HeLa, MCF-7, A549 and the normal cell line BEAS-2B, quantified by real-time polymerase chain reaction (real-time PCR) and flow cytometry, respectively. From that, four cell lines with different levels of FRs, were chosen for cytotoxicity assays of MTX and CDEnFA:MTX using the MTT assay. Real-time PCR and flow cytometry data demonstrated that all cell lines ubiquitously express moderate levels of RFC. These experiments have also shown that levels of FR protein in CaCo-2 cells are high, while levels in SKOV-3, HeLa and MCF-7 cells are moderate. A549 and BEAS-2B cells express low levels of FR protein. FRs are highly expressed in all the cancer cell lines analysed when compared to the normal cell line BEAS-2B. The cell lines CaCo-2, MCF-7, A549 and BEAS-2B were used in the cell viability assays. 48 hours treatment with the free drug and the complex resulted in IC50 values of 93.9 µM ± 15.2 and 56.0 µM ± 4.0 for CaCo-2 for free MTX and CDEnFA:MTX respectively, 118.2 µM ± 16.8 and 97.8 µM ± 12.3 for MCF-7, 36.4 µM ± 6.9 and 75.0 µM ± 10.5 for A549 and 132.6 µM ± 16.1 and 288.1 µM ± 26.3 for BEAS-2B. These results demonstrate that free MTX is more toxic towards cell lines expressing low levels of FR, such as the BEAS-2B. More importantly, these results demonstrate that the inclusion complex CDEnFA:MTX showed greater cytotoxicity than the free drug towards the high FR expressing CaCo-2 cells, indicating that it has potential to target this receptor, enhancing the specificity and the efficiency of the drug. The use of cell imaging by confocal microscopy has allowed visualisation of FR targeting in cancer cells, as well as the identification of the interlisation pathway of the drug. Hence, the cellular uptake and internalisation process of this drug delivery system is being addressed.Keywords: cancer treatment, cyclodextrins, drug delivery, folate receptors, reduced folate carriers
Procedia PDF Downloads 3082650 An Extraction of Cancer Region from MR Images Using Fuzzy Clustering Means and Morphological Operations
Authors: Ramandeep Kaur, Gurjit Singh Bhathal
Abstract:
Cancer diagnosis is very difficult task. Magnetic resonance imaging (MRI) scan is used to produce image of any part of the body and provides an efficient way for diagnosis of cancer or tumor. In existing method, fuzzy clustering mean (FCM) is used for the diagnosis of the tumor. In the proposed method FCM is used to diagnose the cancer of the foot. FCM finds the centroids of the clusters of the foot cancer obtained from MRI images. FCM thresholding result shows the extract region of the cancer. Morphological operations are applied to get extracted region of cancer.Keywords: magnetic resonance imaging (MRI), fuzzy C mean clustering, segmentation, morphological operations
Procedia PDF Downloads 3932649 Mammographic Multi-View Cancer Identification Using Siamese Neural Networks
Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin
Abstract:
Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network
Procedia PDF Downloads 1292648 Cellular Targeting to Dual Gaseous Microenvironments by Polydimethylsiloxane Microchip
Authors: Samineh Barmaki, Ville Jokinen, Esko Kankuri
Abstract:
We report a microfluidic chip that can be used to modify the gaseous microenvironment of a cell-culture in ambient atmospheric conditions. The aim of the study is to show the cellular response to nitric oxide (NO) under hypoxic (oxygen < 5%) condition. Simultaneously targeting to hypoxic and nitric oxide will provide an opportunity for NO‑based therapeutics. Studies on cellular responses to lowered oxygen concentration or to gaseous mediators are usually carried out under a specific macro environment, such as hypoxia chambers, or with specific NO donor molecules that may have additional toxic effects. In our study, the chip consists of a microfluidic layer and a cell culture well, separated by a thin gas permeable polydimethylsiloxane (PDMS) membrane. The main design goal is to separate the gas oxygen scavenger and NO donor solutions, which are often toxic, from the cell media. Two different types of gas exchangers, titled 'pool' and 'meander' were tested. We find that the pool design allows us to reach a higher level of oxygen depletion than meander (24.32 ± 19.82 %vs -3.21 ± 8.81). Our microchip design can make the cells culture more simple and makes it easy to adapt existing cell culture protocols. Our first application is utilizing the chip to create hypoxic conditions on targeted areas of cell culture. In this study, oxygen scavenger sodium sulfite generates hypoxia and its effect on human embryonic kidney cells (HEK-293). The PDMS membrane was coated with fibronectin before initiating cell cultures, and the cells were grown for 48h on the chips before initiating the gas control experiments. The hypoxia experiments were performed by pumping of O₂-depleted H₂O into the microfluidic channel with a flow-rate of 0.5 ml/h. Image-iT® reagent as an oxygen level responser was mixed with HEK-293 cells. The fluorescent signal appears on cells stained with Image-iT® hypoxia reagent (after 6h of pumping oxygen-depleted H₂O through the microfluidic channel in pool area). The exposure to different levels of O₂ can be controlled by varying the thickness of the PDMS membrane. Recently, we improved the design of the microfluidic chip, which can control the microenvironment of two different gases at the same time. The hypoxic response was also improved from the new design of microchip. The cells were grown on the thin PDMS membrane for 30 hours, and with a flowrate of 0.1 ml/h; the oxygen scavenger was pumped into the microfluidic channel. We also show that by pumping sodium nitroprusside (SNP) as a nitric oxide donor activated under light and can generate nitric oxide on top of PDMS membrane. We are aiming to show cellular microenvironment response of HEK-293 cells to both nitric oxide (by pumping SNP) and hypoxia (by pumping oxygen scavenger solution) in separated channels in one microfluidic chip.Keywords: hypoxia, nitric oxide, microenvironment, microfluidic chip, sodium nitroprusside, SNP
Procedia PDF Downloads 1272647 Archetypes in the Rorschach Inkblots: Imparting Universal Meaning in the Face of Ambiguity
Authors: Donna L. Roberts
Abstract:
The theory of archetypes contends that themes based on universal foundational images reside in and are transmitted generationally through the collective unconscious, which is referenced throughout an individual’s experience in order to make sense of that experience. There is then, a profoundly visceral and instinctive agreement on the gestalt of these universal themes and how they apply to the human condition throughout space and time. The inherent nature of projective tests, such as the Rorschach Inkblot, necessitates that the stimulus is ambiguous and thus elicits responses that reflect the unconscious inner psyche of the respondent. As the development of the Rorschach inkblots was relatively random and serendipitous - i.e., the inkblots were not engineered to elicit a specifically defined response - it would stand to reason that without a collective unconscious, every individual would interpret the inkblots in an individualized and unique way. Yet this is not the case. Instead, common themes appear in the images of the inkblots and their interpretation that reflect this deeper iconic understanding. This study analyzed the ten Rorschach inkblots in terms of Jungian archetypes, both with respect to the form of images on each plate and the commonly observed themes in responses. Examples of the archetypes were compared to each of the inkblots, with subsequent descriptions matched to the standard responses. The findings yielded clear and distinct instances of the universal symbolism intrinsic in the inkblot images as well as ubiquitous throughout the responses. This project illustrates the influence of the theories of psychologist Carl Gustav Jung on the interpretation of the ambiguous stimuli. It further serves to demonstrate the merit of Jungian psychology as a valuable tool with which to understand the nature of projective tests in general, Rorschach’s work specifically, and ultimately the broader implications for our collective unconscious and common humanity.Keywords: archetypes, inkblots, projective tests, Rorschach
Procedia PDF Downloads 1012646 An Experiment of Three-Dimensional Point Clouds Using GoPro
Authors: Jong-Hwa Kim, Mu-Wook Pyeon, Yang-dam Eo, Ill-Woong Jang
Abstract:
Construction of geo-spatial information recently tends to develop as multi-dimensional geo-spatial information. People constructing spatial information is also expanding its area to the general public from some experts. As well as, studies are in progress using a variety of devices, with the aim of near real-time update. In this paper, getting the stereo images using GoPro device used widely also to the general public as well as experts. And correcting the distortion of the images, then by using SIFT, DLT, is acquired the point clouds. It presented a possibility that on the basis of this experiment, using a video device that is readily available in real life, to create a real-time digital map.Keywords: GoPro, SIFT, DLT, point clouds
Procedia PDF Downloads 4632645 Secure Image Encryption via Enhanced Fractional Order Chaotic Map
Authors: Ismail Haddad, Djamel Herbadji, Aissa Belmeguenai, Selma Boumerdassi
Abstract:
in this paper, we provide a novel approach for image encryption that employs the Fibonacci matrix and an enhanced fractional order chaotic map. The enhanced map overcomes the drawbacks of the classical map, especially the limited chaotic range and non-uniform distribution of chaotic sequences, resulting in a larger encryption key space. As a result, this strategy improves the encryption system's security. Our experimental results demonstrate that our proposed algorithm effectively encrypts grayscale images with exceptional efficiency. Furthermore, our technique is resistant to a wide range of potential attacks, including statistical and entropy attacks.Keywords: image encryption, logistic map, fibonacci matrix, grayscale images
Procedia PDF Downloads 3082644 Designing Agricultural Irrigation Systems Using Drone Technology and Geospatial Analysis
Authors: Yongqin Zhang, John Lett
Abstract:
Geospatial technologies have been increasingly used in agriculture for various applications and purposes in recent years. Unmanned aerial vehicles (drones) fit the needs of farmers in farming operations, from field spraying to grow cycles and crop health. In this research, we conducted a practical research project that used drone technology to design and map optimal locations and layouts of irrigation systems for agriculture farms. We flew a DJI Mavic 2 Pro drone to acquire aerial remote sensing images over two agriculture fields in Forest, Mississippi, in 2022. Flight plans were first designed to capture multiple high-resolution images via a 20-megapixel RGB camera mounted on the drone over the agriculture fields. The Drone Deploy web application was then utilized to develop flight plans and subsequent image processing and measurements. The images were orthorectified and processed to estimate the area of the area and measure the locations of the water line and sprinkle heads. Field measurements were conducted to measure the ground targets and validate the aerial measurements. Geospatial analysis and photogrammetric measurements were performed for the study area to determine optimal layout and quantitative estimates for irrigation systems. We created maps and tabular estimates to demonstrate the locations, spacing, amount, and layout of sprinkler heads and water lines to cover the agricultural fields. This research project provides scientific guidance to Mississippi farmers for a precision agricultural irrigation practice.Keywords: drone images, agriculture, irrigation, geospatial analysis, photogrammetric measurements
Procedia PDF Downloads 672643 A General Framework for Knowledge Discovery Using High Performance Machine Learning Algorithms
Authors: S. Nandagopalan, N. Pradeep
Abstract:
The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.Keywords: active contour, bayesian, echocardiographic image, feature vector
Procedia PDF Downloads 4132642 Image-Based UAV Vertical Distance and Velocity Estimation Algorithm during the Vertical Landing Phase Using Low-Resolution Images
Authors: Seyed-Yaser Nabavi-Chashmi, Davood Asadi, Karim Ahmadi, Eren Demir
Abstract:
The landing phase of a UAV is very critical as there are many uncertainties in this phase, which can easily entail a hard landing or even a crash. In this paper, the estimation of relative distance and velocity to the ground, as one of the most important processes during the landing phase, is studied. Using accurate measurement sensors as an alternative approach can be very expensive for sensors like LIDAR, or with a limited operational range, for sensors like ultrasonic sensors. Additionally, absolute positioning systems like GPS or IMU cannot provide distance to the ground independently. The focus of this paper is to determine whether we can measure the relative distance and velocity of UAV and ground in the landing phase using just low-resolution images taken by a monocular camera. The Lucas-Konda feature detection technique is employed to extract the most suitable feature in a series of images taken during the UAV landing. Two different approaches based on Extended Kalman Filters (EKF) have been proposed, and their performance in estimation of the relative distance and velocity are compared. The first approach uses the kinematics of the UAV as the process and the calculated optical flow as the measurement; On the other hand, the second approach uses the feature’s projection on the camera plane (pixel position) as the measurement while employing both the kinematics of the UAV and the dynamics of variation of projected point as the process to estimate both relative distance and relative velocity. To verify the results, a sequence of low-quality images taken by a camera that is moving on a specifically developed testbed has been used to compare the performance of the proposed algorithm. The case studies show that the quality of images results in considerable noise, which reduces the performance of the first approach. On the other hand, using the projected feature position is much less sensitive to the noise and estimates the distance and velocity with relatively high accuracy. This approach also can be used to predict the future projected feature position, which can drastically decrease the computational workload, as an important criterion for real-time applications.Keywords: altitude estimation, drone, image processing, trajectory planning
Procedia PDF Downloads 1052641 Geographical Data Visualization Using Video Games Technologies
Authors: Nizar Karim Uribe-Orihuela, Fernando Brambila-Paz, Ivette Caldelas, Rodrigo Montufar-Chaveznava
Abstract:
In this paper, we present the advances corresponding to the implementation of a strategy to visualize geographical data using a Software Development Kit (SDK) for video games. We use multispectral images from Landsat 7 platform and Laser Imaging Detection and Ranging (LIDAR) data from The National Institute of Geography and Statistics of Mexican (INEGI). We select a place of interest to visualize from Landsat platform and make some processing to the image (rotations, atmospheric correction and enhancement). The resulting image will be our gray scale color-map to fusion with the LIDAR data, which was selected using the same coordinates than in Landsat. The LIDAR data is translated to 8-bit raw data. Both images are fused in a software developed using Unity (an SDK employed for video games). The resulting image is then displayed and can be explored moving around. The idea is the software could be used for students of geology and geophysics at the Engineering School of the National University of Mexico. They will download the software and images corresponding to a geological place of interest to a smartphone and could virtually visit and explore the site with a virtual reality visor such as Google cardboard.Keywords: virtual reality, interactive technologies, geographical data visualization, video games technologies, educational material
Procedia PDF Downloads 2382640 Assessing Image Quality in Mobile Radiography: A Phantom-Based Evaluation of a New Lightweight Mobile X-Ray Equipment
Authors: May Bazzi, Shafik Tokmaj, Younes Saberi, Mats Geijer, Tony Jurkiewicz, Patrik Sund, Anna Bjällmark
Abstract:
Mobile radiography, employing portable X-ray equipment, has become a routine procedure within hospital settings, with chest X-rays in intensive care units standing out as the most prevalent mobile X-ray examinations. This approach is not limited to hospitals alone, as it extends its benefits to imaging patients in various settings, particularly those too frail to be transported, such as elderly care residents in nursing homes. Moreover, the utility of mobile X-ray isn't confined solely to traditional healthcare recipients; it has proven to be a valuable resource for vulnerable populations, including the homeless, drug users, asylum seekers, and patients with multiple co-morbidities. Mobile X-rays reduce patient stress, minimize costly hospitalizations, and offer cost-effective imaging. While studies confirm its reliability, further research is needed, especially regarding image quality. Recent advancements in lightweight equipment with enhanced battery and detector technology provide the potential for nearly handheld radiography. The main aim of this study was to evaluate a new lightweight mobile X-ray system with two different detectors and compare the image quality with a modern stationary system. Methods: A total of 74 images of the chest (chest anterior-posterior (AP) views and chest lateral views) and pelvic/hip region (AP pelvis views, hip AP views, and hip cross-table lateral views) were acquired on a whole-body phantom (Kyotokagaku, Japan), utilizing varying image parameters. These images were obtained using a stationary system - 18 images (Mediel, Sweden), a mobile X-ray system with a second-generation detector - 28 images (FDR D-EVO II; Fujifilm, Japan) and a mobile X-ray system with a third-generation detector - 28 images (FDR D-EVO III; Fujifilm, Japan). Image quality was assessed by visual grading analysis (VGA), which is a method to measure image quality by assessing the visibility and accurate reproduction of anatomical structures within the images. A total of 33 image criteria were used in the analysis. A panel of two experienced radiologists, two experienced radiographers, and two final-term radiographer students evaluated the image quality on a 5-grade ordinal scale using the software Viewdex 3.0 (Viewer for Digital Evaluation of X-ray images, Sweden). Data were analyzed using visual grading characteristics analysis. The dose was measured by the dose-area product (DAP) reported by the respective systems. Results: The mobile X-ray equipment (both detectors) showed significantly better image quality than the stationary equipment for the pelvis, hip AP and hip cross-table lateral images with AUCVGA-values ranging from 0.64-0.92, while chest images showed mixed results. The number of images rated as having sufficient quality for diagnostic use was significantly higher for mobile X-ray generation 2 and 3 compared with the stationary X-ray system. The DAP values were higher for the stationary compared to the mobile system. Conclusions: The new lightweight radiographic equipment had an image quality at least as good as a fixed system at a lower radiation dose. Future studies should focus on clinical images and consider radiographers' viewpoints for a comprehensive assessment.Keywords: mobile x-ray, visual grading analysis, radiographer, radiation dose
Procedia PDF Downloads 542639 Enhancing Learning Ability among Deaf Students by Using Photographic Images
Authors: Aidah Alias, Mustaffa Halabi Azahari, Adzrool Idzwan Ismail, Salasiah Ahmad
Abstract:
Education is one of the most important elements in a human life. Educations help us in learning and achieve new things in life. The ability of hearing gave us chances to hear voices and it is important in our communication. Hearing stories told by others; hearing news and music to create our creative and sense; seeing and hearing make us understand directly the message trying to deliver. But, what will happen if we are born deaf or having hearing loss while growing up? The objectives of this paper are to identify the current practice in teaching and learning among deaf students and to analyse an appropriate method in enhancing learning process among deaf students. A case study method was employed by using methods of observation and interview to selected deaf students and teachers. The findings indicated that the suitable method of teaching for deaf students is by using pictures and body movement. In other words, by combining these two medium of images and body movement, the best medium that the study suggested is by using video or motion pictures. The study concluded and recommended that video or motion pictures is recommended medium to be used in teaching and learning for deaf students.Keywords: deaf, photographic images, visual communication, education, learning ability
Procedia PDF Downloads 2822638 Covid-19, Diagnosis with Computed Tomography and Artificial Intelligence, in a Few Simple Words
Authors: Angelis P. Barlampas
Abstract:
Target: The (SARS-CoV-2) is still a threat. AI software could be useful, categorizing the disease into different severities and indicate the extent of the lesions. Materials and methods: AI is a new revolutionary technique, which uses powered computerized systems, to do what a human being does more rapidly, more easily, as accurate and diagnostically safe as the original medical report and, in certain circumstances, even better, saving time and helping the health system to overcome problems, such as work overload and human fatigue. Results: It will be given an effort to describe to the inexperienced reader (see figures), as simple as possible, how an artificial intelligence system diagnoses computed tomography pictures. First, the computerized machine learns the physiologic motives of lung parenchyma by being feeded with normal structured images of the lung tissue. Having being used to recognizing normal structures, it can then easily indentify the pathologic ones, as their images do not fit to known normal picture motives. It is the same way as when someone spends his free time in reading magazines with quizzes, such as <Keywords: covid-19, artificial intelligence, automated imaging, CT, chest imaging
Procedia PDF Downloads 462637 Looking beyond Lynch's Image of a City
Authors: Sandhya Rao
Abstract:
Kevin Lynch’s Theory on Imeageability, let on explore a city in terms of five elements, Nodes, Paths, Edges, landmarks and Districts. What happens when we try to record the same data in an Indian context? What happens when we apply the same theory of Imageability to a complex shifting urban pattern of the Indian cities and how can we as Urban Designers demonstrate our role in the image building ordeal of these cities? The organizational patterns formed through mental images, of an Indian city is often diverse and intangible. It is also multi layered and temporary in terms of the spirit of the place. The pattern of images formed is loaded with associative meaning and intrinsically linked with the history and socio-cultural dominance of the place. The embedded memory of a place in one’s mind often plays an even more important role while formulating these images. Thus while deriving an image of a city one is often confused or finds the result chaotic. The images formed due to its complexity are further difficult to represent using a single medium. Under such a scenario it’s difficult to derive an output of an image constructed as well as make design interventions to enhance the legibility of a place. However, there can be a combination of tools and methods that allows one to record the key elements of a place through time, space and one’s user interface with the place. There has to be a clear understanding of the participant groups of a place and their time and period of engagement with the place as well. How we can translate the result obtained into a design intervention at the end, is the main of the research. Could a multi-faceted cognitive mapping be an answer to this or could it be a very transient mapping method which can change over time, place and person. How does the context influence the process of image building in one’s mind? These are the key questions that this research will aim to answer.Keywords: imageability, organizational patterns, legibility, cognitive mapping
Procedia PDF Downloads 3072636 Liver Regeneration of Small in situ Injury
Authors: Ziwei Song, Junjun Fan, Jeremy Teo, Yang Yu, Yukun Ma, Jie Yan, Shupei Mo, Lisa Tucker-Kellogg, Peter So, Hanry Yu
Abstract:
Liver is the center of detoxification and exposed to toxic metabolites all the time. It is highly regenerative after injury, with the ability to restore even after 70% partial hepatectomy. Most of the previous studies were using hepatectomy as injury models for liver regeneration study. There is limited understanding of small-scale liver injury, which can be caused by either low dose drug consumption or hepatocyte routine metabolism. Although these small in situ injuries do not cause immediate symptoms, repeated injuries will lead to aberrant wound healing in liver. Therefore, the cellular dynamics during liver regeneration is critical for our understanding of liver regeneration mechanism. We aim to study the liver regeneration of small-scale in situ liver injury in transgenic mice labeling actin (Lifeact-GFP). Previous studies have been using sample sections and biopsies of liver, which lack real-time information. In order to trace every individual hepatocyte during the regeneration process, we have developed and optimized an intravital imaging system that allows in vivo imaging of mouse liver for consecutive 5 days, allowing real-time cellular tracking and quantification of hepatocytes. We used femtosecond-laser ablation to make controlled and repeatable liver injury model, which mimics the real-life small in situ liver injury. This injury model is the first case of its kind for in vivo study on liver. We found that small-scale in situ liver injury is repaired by the coordination of hypertrophy and migration of hepatocytes. Hypertrophy is only transient at initial phase, while migration is the main driving force to complete the regeneration process. From cellular aspect, Akt/mTOR pathway is activated immediately after injury, which leads to transient hepatocyte hypertrophy. From mechano-sensing aspect, the actin cable, formed at apical surface of wound proximal hepatocytes, provides mechanical tension for hepatocyte migration. This study provides important information on both chemical and mechanical signals that promote liver regeneration of small in situ injury. We conclude that hypertrophy and migration play a dominant role at different stages of liver regeneration.Keywords: hepatocyte, hypertrophy, intravital imaging, liver regeneration, migration
Procedia PDF Downloads 2022635 Rasagiline Improves Metabolic Function and Reduces Tissue Injury in the Substantia Nigra in Parkinson's Disease: A Longitudinal In-Vivo Advanced MRI Study
Authors: Omar Khan, Shana Krstevska, Edwin George, Veronica Gorden, Fen Bao, Christina Caon, NP-C, Carla Santiago, Imad Zak, Navid Seraji-Bozorgzad
Abstract:
Objective: To quantify cellular injury in the substantia nigra (SN) in patients with Parkinson's disease (PD) and to examine the effect of rasagiline of tissue injury in the SN in patients with PD. Background: N-acetylaspartate (NAA) quantified with MRS is a reliable marker of neuronal metabolic function. Fractional anisotropy (FA) and mean diffusivity (MD) obtained with DTI, characterize tissue alignment and integrity. Rasagline, has been shown to exert anti-apototic effect. We applied these advanced MRI techniques to examine: (i) the effect of rasagiline on cellular injury and metabolism in patients with early PD, and (ii) longitudinal changes seen over time in PD. Methods: We conducted a prospective longitudinal study in patients with mild PD, naive to dopaminergic treatment. The imaging protocol included multi-voxel proton-MRS and DTI of the SN, acquired on a 3T scanner. Scans were performed at baseline and month 3, during which the patient was on no treatment. At that point, rasagiline 1 mg orally daily was initiated and MRI scans are were obtained at 6 and 12 months after starting rasagiline. The primary objective was to compare changes during the 3-month period of “no treatment” to the changes observed “on treatment” with rasagiline at month 12. Age-matched healthy controls were also imaged. Image analysis was performed blinded to treatment allocation and period. Results: 25 patients were enrolled in this study. Compared to the period of “no treatment”, there was significant increase in the NAA “on treatment” period (-3.04 % vs +10.95 %, p= 0.0006). Compared to the period of “no treatment”, there was significant increase in following 12 month in the FA “on treatment” (-4.8% vs +15.3%, p<0.0001). The MD increased during “no treatment” and decreased in “on treatment” (+2.8% vs -7.5%, p=0.0056). Further analysis and clinical correlation are ongoing. Conclusions: Advanced MRI techniques quantifying cellular injury in the SN in PD is a feasible approach to investigate dopaminergic neuronal injury and could be developed as an outcome in exploratory studies. Rasagiline appears to have a stabilizing effect on dopaminergic cell loss and metabolism in the SN in PD, that warrants further investigation in long-term studies.Keywords: substantia nigra, Parkinson's disease, MRI, neuronal loss, biomarker
Procedia PDF Downloads 3082634 A Comparative Study of Deep Learning Methods for COVID-19 Detection
Authors: Aishrith Rao
Abstract:
COVID 19 is a pandemic which has resulted in thousands of deaths around the world and a huge impact on the global economy. Testing is a huge issue as the test kits have limited availability and are expensive to manufacture. Using deep learning methods on radiology images in the detection of the coronavirus as these images contain information about the spread of the virus in the lungs is extremely economical and time-saving as it can be used in areas with a lack of testing facilities. This paper focuses on binary classification and multi-class classification of COVID 19 and other diseases such as pneumonia, tuberculosis, etc. Different deep learning methods such as VGG-19, COVID-Net, ResNET+ SVM, Deep CNN, DarkCovidnet, etc., have been used, and their accuracy has been compared using the Chest X-Ray dataset.Keywords: deep learning, computer vision, radiology, COVID-19, ResNet, VGG-19, deep neural networks
Procedia PDF Downloads 151