Results 11 to 20 of about 10,752 (167)
Deep Learning Models for Calculation of Cardiothoracic Ratio from Chest Radiographs for Assisted Diagnosis of Cardiomegaly [PDF]
arXiv, 2021 We propose an automated method based on deep learning to compute the cardiothoracic ratio and detect the presence of cardiomegaly from chest radiographs. We develop two separate models to demarcate the heart and chest regions in an X-ray image using bounding boxes and use their outputs to calculate the cardiothoracic ratio. We obtain a sensitivity of 0.
Tanveer Gupte +5 more
arxiv +3 more sources
Deep learning‐based high‐dimensional multiple regression estimator for chest x‐ray image classification in rapid cardiomegaly screening [PDF]
Translational Biophotonics, 2023 Chest x‐ray (CXR) examination is a common first‐line, non‐invasive, and rapid screening method in clinical examinations. The posteroanterior (PA) and anteroposterior (AP) view modes can both be used to detect related cardiopulmonary diseases, such as ...
Pi‐Yun Chen +4 more
doaj +2 more sources
Unsupervised domain adaptation for the detection of cardiomegaly in cross-domain chest X-ray images [PDF]
Frontiers in Artificial Intelligence, 2023 In recent years, several deep learning approaches have been successfully applied in the field of medical image analysis. More specifically, different deep neural network architectures have been proposed and assessed for the detection of various ...
Patrick Thiam +6 more
doaj +2 more sources
Longitudinal detection of radiological abnormalities with time-modulated LSTM [PDF]
DLMIA/ML-CDS@MICCAI 2018, 2018 Convolutional neural networks (CNNs) have been successfully employed in recent years for the detection of radiological abnormalities in medical images such as plain x-rays.
A Esteva +3 more
core +2 more sources
Assessing Cardiomegaly in Dogs Using a Simple CNN Model [PDF]
arXivThis paper introduces DogHeart, a dataset comprising 1400 training, 200 validation, and 400 test images categorized as small, normal, and large based on VHS score. A custom CNN model is developed, featuring a straightforward architecture with 4 convolutional layers and 4 fully connected layers.
Nikhil Deekonda
arxiv +3 more sources
Journal of Emergencies, Trauma and Shock, 2010 An infant with Down′s syndrome was noted to have hypoxemia and tachypnea at birth. The clinical examination, electrocardiogram (ECG) and the chest X-ray findings suggested a specific diagnosis that is not usually associated with Down′s ...
Upadhyay Shailendra +2 more
doaj +2 more sources
Diagnosis and precise localization of cardiomegaly disease using U-NET
Informatics in Medicine Unlocked, 2020 This study examines an end-to-end technique which uses a Deep Convolutional Neural Network U-Net based architecture to detect Cardiomegaly disease. The learning phase is achieved by using Chest X-ray images extracted from the “ChestX-ray8” open source ...
Abdelilah Bouslama +2 more
doaj +2 more sources
A study on computed tomography cardiothoracic ratio in predicting left ventricular systolic dysfunction [PDF]
Clinical and Experimental Emergency Medicine, 2023 Objective A cardiothoracic ratio ≥0.50 is widely used as an indicator of cardiomegaly, but associations between the cardiothoracic ratio and left ventricular systolic dysfunction (LVSD) have not been investigated previously.
Minki Chae +3 more
doaj +1 more source
Journal of Community Hospital Internal Medicine Perspectives, 2021 Background Chest radiographs can identify important abnormalities in patients undergoing diagnostic evaluation for cardiovascular diseases. Cardiomegaly often reflects cardiac chamber dilation, or cardiac muscle hypertrophy, or both conditions.
Benjamin Daines +8 more
doaj +1 more source
Journal of Association of Pulmonologist of Tamil Nadu, 2021 Introduction: Asymptomatic individuals may have unnoticed pulmonary lesions (PL) in the form of infective, noninfective, and neoplastic etiology. Earlier studies detected pulmonary pathology in chest radiographs of health checkup patients and this helped
Ajai Ramcharan Kattoju +5 more
doaj +1 more source