Results 1 to 10 of about 29,862 (247)

A newborn with cardiomegaly

open access: goldJournal 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   +5 more sources

Diagnosis and precise localization of cardiomegaly disease using U-NET

open access: goldInformatics 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   +3 more sources

The clinical associations with cardiomegaly in patients undergoing evaluation for pulmonary hypertension

open access: yesJournal 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   +2 more sources

The Association of Salivary Conductivity with Cardiomegaly in Hemodialysis Patients

open access: yesApplied Sciences, 2021
Patients on maintenance hemodialysis are at high risk for cardiovascular morbidity and mortality. Fluid overload is generally regarded as the main cause of cardiovascular death among them.
An-Ting Lee   +6 more
doaj   +2 more sources

Chest X-Ray Image Analysis With Combining 2D and 1D Convolutional Neural Network Based Classifier for Rapid Cardiomegaly Screening [PDF]

open access: goldIEEE Access, 2022
Cardiomegaly is an asymptomatic disease. Symptoms, such as palpitations, chest tightness, and shortness of breath, may be the early indications of cardiac hypertrophy, which can be divided into cardiac hypertrophy and ventricular enlargement.
Jian‐Xing Wu   +5 more
openalex   +2 more sources

Familial Idiopathic Cardiomegaly [PDF]

open access: bronzeCirculation, 1961
Two young adult sisters are described with clinical and pathologic findings of myocardial disease. These cases along with a suggestive family history are presented as examples of familial idiopathic cardiomegaly. Pathologic findings are compared and contrasted with those in the literature, and etiologic concepts are discussed.
Wayne H. Schrader   +3 more
openalex   +4 more sources

Evaluation of the feasibility of explainable computer-aided detection of cardiomegaly on chest radiographs using deep learning [PDF]

open access: goldScientific Reports, 2021
We examined the feasibility of explainable computer-aided detection of cardiomegaly in routine clinical practice using segmentation-based methods. Overall, 793 retrospectively acquired posterior–anterior (PA) chest X-ray images (CXRs) of 793 patients ...
Mu Sook Lee   +7 more
openalex   +2 more sources

Vertebral Heart Score and Vertebral Left Atrial Size as Radiographic Measurements for Cardiac Size in Dogs—A Literature Review [PDF]

open access: yesAnimals
Radiology plays an important role in veterinary cardiology, along with other methods, such as electrocardiography, echocardiography, and biomarkers, in the diagnosis of cardiac diseases.
Radu Andrei Baisan, Vasile Vulpe
doaj   +2 more sources

Deep Learning Models for Calculation of Cardiothoracic Ratio from Chest Radiographs for Assisted Diagnosis of Cardiomegaly [PDF]

open access: green2021 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD), 2021
We propose an automated method based on deep learning to compute the cardiothoracic ratio and detect the presence of cardiomegaly from chest radiographs.
Tanveer Gupte   +5 more
openalex   +3 more sources

Cardiomegaly Detection on Chest Radiographs: Segmentation Versus Classification

open access: yesIEEE Access, 2020
In this study, we investigate the detection of cardiomegaly on frontal chest radiographs through two alternative deep-learning approaches - via anatomical segmentation and via image-level classification.
Ecem Sogancioglu   +5 more
doaj   +2 more sources

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