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77 articles for “X-Ray Images”
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Detection of Pneumonia in COVID-19 Patients Using X-ray Images
Abstract: This study explores the use of chest X-ray image analysis and deep learning methods to identify pneumonia in COVID-19 patients. Due to the pandemic, Proper as well as immediate examination of COVID-19 is now essential for patient care and disease control. This study proposes a novel approach that uses convolutional neural networks (CNNs) to automatically predict pneumonia in COVID-19 patients using chest X-ray images. In this study, an X-ray of …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 13–23 Read article
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Advancements in Pneumonia X-Ray Image Detection: A Review
Abstract: Pneumonia remains a primary cause of morbidness and mortality worldwide, necessitating the continuous advancement of diagnostic techniques for timely and accurate detection. Pneumonia is common, it is potentially a life-threatening infection for respiration, poses significant challenges to healthcare systems worldwide. Recently, the arrival of deep learning techniques has stirred up the field of medical imaging, offering promising avenues for enhanced pneumonia detection. In this paper, the advancements in pneumonia detection …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 1, 2025 · pp. 1–11 Read article
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COVID-19 Prediction using X-Ray Images and Deep Learning Model
Abstract: In the year 2019, the novel corona virus was emerged in China. Since, then every individual has put their own self to fight against this pandemic situation. Till April 14, 2022, the total COVID-19 confirmed cases are 500,186,525 and deaths are 6,190,349 worldwide. RT-PCR and Rapid antigen test are the standards for COVID-19 detection by WHO. These both tests are time consuming and costly and also there are higher possibilities …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 2, 2022 · pp. 24–32 Read article
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COVID-19 Detection using Convolutional Neural Network (CNN)
Abstract: Coronavirus disease (COVID-19) is spreading across the whole world and has habitual expressive community spread. The sudden hike in the number of patients with COVID-19, i.e. a new respiration virus has an extreme impact on the healthcare system. There are limited kits for diagnosis, hospital beds for such kind of patients, a limited number of personal protective equipment (PPE) for healthcare temporary staff and limited ventilators. A prediction system based …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 2, 2021 · pp. 22–30 Read article
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Stacked Generalization-Based Deep Learning Approach for Pneumonia Detection
Abstract: The proposed work focuses on a stacked generalization-based approach for diagnosing pneumonia from chest X-ray images. It utilizes regularization, early stopping, and data augmentation to deal with overfitting. It uses safe level SMOTE to deal with class imbalance and attention-based feature fusion to adaptively weigh features based on their importance. It uses two publicly available datasets (RSNA and Kermany) with ground truth provided by expert radiologists. The proposed work used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 20–31 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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Deep Learning-Based Pneumonia Diagnosis: A Comparative Review of Models and Metrics
Abstract: Pneumonia is a common viral infection that affects a large percentage of people worldwide. It is more common in developing and impoverished areas because of factors like poor sanitation, crowded living quarters, pollution in the environment, and restricted access to medical facilities. In order to improve survival chances and gain access to therapeutic therapies, pneumonia must be diagnosed as soon as possible. A type of artificial intelligence called deep learning …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 Read article
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Real-Time YOLOv8l Contraband Detection in X- Ray Security Screening with Automated Identification of Weapons and Hazardous Objects for Threat Alerting
Abstract: A real-time contraband detection system based on YOLOv8l has been proposed for use in very high security installations, such as airports and public screening facilities. The contraband detection system has been trained with curated X-ray contraband datasets containing twelve different object types like firearms, knives, bullets, etc., with the datasets having been constructed to provide an equal number of examples for each object class to support robust detection. The methodology …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 3, 2026 Read article
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Digital Sampling and Testing of COVID-19 to Reduce Lab Procedures Further Decreasing Carbon Emission: Review
Abstract: The COVID-19 pandemic has caused a new virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that primarily infects the lungs and can lead to serious respiratory illnesses such as ARDS and pneumonia caused by coronavirus. Declared a pandemic by the World Health Organization (WHO), the disease belongs to the family of coronaviruses that can cause cold and flu, making it a highly contagious disease. Chest imaging tests such …
Published in Journal of Open Source Developments · Vol. 10, Issue 1, 2023 · pp. 19–25 Read article
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Identifying COVID-19 in chest X-ray and CT scan images through the application of machine learning algorithms.
Abstract: Since the beginning of the current COVID-19 pandemic, more than five million people have been infected and the numbers are still on the rise. Early symptom detection and proper hygienic standards are thus of utmost importance, especially in venues where people are in random or opportunistic contact with each other. To this end, automated systems with medical-grade body temperature measurement, hygienic compliance evaluation and individualized, person-to-person tracking, are essential, not …
Published in Research and Reviews : A Journal of Immunology · Vol. 13, Issue 2, 2023 · pp. 13–21 Read article
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Enhancing Radiographic Dental Image Visualisation with Colourisation and Graphical User
Abstract: Radiography has been used in dentistry to find cavities, bone loss, hidden dental structures, tumour, and cysts. Due to the monochromatic characteristic of X-ray images, it is difficult to discern disorders and explain the diagnosis procedure. Enhance the visualization of X-rays is one of the ways to ease the work of the dentist. There were several studies to enhance visualization by giving pseudo colour shades to monochromatic images. The conclusion …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 7, Issue 2, 2020 · pp. 7–19 Read article
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Pneumonia Detection and Classification Using Deep Learning
Abstract: Pneumonia, an infectious lung disease primarily caused by bacteria, often exacerbated by environmental factors, leads to the accumulation of pus in the lung’s alveoli. Accurate diagnosis through chest X-rays, ultrasounds, or lung biopsies is crucial to avoid misdiagnosis and ensure proper treatment, crucial for patients’ quality of life. Diagnostic capacities have been greatly improved by deep learning advances, especially with convolutional neural networks (CNNs). This research presents a robust CNN-based …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 9–19 Read article
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Robust Fruit/Vegetable Quality Assessment Using Nondestructive Textural Distortion Analysis
Abstract: A nondestructive approach for fruit quality assessment is outlined in this paper. An x-ray based image analysis for the internal quality assessment is presented. The quality assessment with external inspection is constraint only to the shape ,color and texture, the quality analysis for the internal effects were not possible. The Nondestructive approach using an x-ray image of a testing sample is processed, where the textural spectral variation and pattern distortion …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 2, 2018 · pp. 38–47 Read article
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X-Ray Insight: Deep Learning-Enhanced Detection and Grading of Knee Osteoarthritis
Abstract: Osteoarthritis (OA) is the most prevalent form of arthritis affecting the knee. It is a degenerative joint disease characterized by the gradual deterioration of cartilage, typically impacting individuals aged 50 and above, although it can also occur in younger people. The condition progresses slowly, with symptoms intensifying over time, leading to significant pain and discomfort. Early diagnosis and intervention can significantly alleviate pain and enhance the quality of life for …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 2, Issue 2, 2024 · pp. 1–6 Read article
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Smart Diagnosis Using Machine Learning
Abstract: We discuss a plausible way for smart diagnosis. Theuse of Deep Learning in image processing can enable us to build Models to detect the presence of ailments in Diagnostic Images such as X-Ray or CT Scans performing as a diagnosis tool. These trained models can be effortlessly added into an easily accessible portal like a website or a phone application providing ease of use even for a non-practitioner. Further, we …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 2, 2020 · pp. 39–45 Read article
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Automatic Chest X-ray Report Generation Using Machine Learning
Abstract: In this study, a deep neural network is suggested for the automatic creation of precise radiologist reports from chest X-ray pictures. The proposed network responds to the need for medical image captioning by learning to extract key features from the image and creating tag embeddings for each patient's X-ray images. Medical image captioning demands coherence and high accuracy in identifying abnormalities and extracting information. For a finer representation, the network …
Published in Journal of Instrumentation Technology & Innovations · Vol. 13, Issue 1, 2023 · pp. 29–39 Read article
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COVID-19 Detection through Deep Learning Models using Chest X-ray
Abstract: Detection of COVID-19 in a minimum amount of time is one of the biggest challenges in front of us because COVID-19 is a rapidly spreading disease. Patients are increasing in a rapid amount of time. Hence, we proposed an AI-technique based deep-convolutional neural network to detect COVID-19 patients using real-world data. In our proposed system, chest X-ray images are used to find out COVID- 19 patients. X-rays are available very …
Published in Journal of Advancements in Robotics · Vol. 8, Issue 2, 2021 · pp. 11–16 Read article
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DentiDetect: Dental Diagnosis Powered by Deep Learning
Abstract: Dental X-rays play a crucial role in modern dentistry, enabling dentists to detect cavities, bone loss, and other hidden dental issues that are not easily visible during a routine examination. X-rays offer a clear picture of teeth, bones, and nearby tissues, enabling early identification of issues. This helps create more efficient treatment strategies and improves patient outcomes. Three commonly used types of X-rays include bitewing, periapical, and panoramic. Bitewing X-rays …
Published in Research and Reviews: A Journal of Dentistry · Vol. 15, Issue 3, 2024 · pp. 21–26 Read article
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Comparative Study on Methods for Teeth Image Recognition
Abstract: This article proposes a new method to find a specific tooth from the digital picture of multiple teeth. The modified methods can significantly simplify the pattern recognition process for teeth. Here we compared some of the popular recognition method like principal component analysis (PCA) and hybrid differential method (HDM). These methods are lot more simple, runs faster and the identification rate is better. These approaches will reduce the traditional reliance …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 3, 2014 · pp. 22–31 Read article
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Pneumonia Identification Using Explainable Artificial Intelligence
Abstract: Pneumonia, including tuberculosis (TB), remains one of the leading causes of death worldwide, especially in regions where access to healthcare is limited. Early and accurate diagnosis is critical for effective treatment and better patient outcomes, but traditional methods are time-consuming and require specialized expertise. This study explores the use of advanced deep learning models VGG16, VGG19, and ResNet50 to detect pneumonia and TB from chest X-ray images. By leveraging transfer …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 01–11 Read article