AI Medical Compendium Topic:
Radiographic Image Interpretation, Computer-Assisted

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COVID-19 Diagnosis Using an Enhanced Inception-ResNetV2 Deep Learning Model in CXR Images.

Journal of healthcare engineering
The COVID-19 pandemic has a significant negative effect on people's health, as well as on the world's economy. Polymerase chain reaction (PCR) is one of the main tests used to detect COVID-19 infection. However, it is expensive, time-consuming, and l...

Enhanced Diagnosis of Pneumothorax with an Improved Real-Time Augmentation for Imbalanced Chest X-rays Data Based on DCNN.

IEEE/ACM transactions on computational biology and bioinformatics
Pneumothorax is a common pulmonary disease that can lead to dyspnea and can be life-threatening. X-ray examination is the main means to diagnose this disease. Computer-aided diagnosis of pneumothorax on chest X-ray, as a prerequisite for a timely cur...

A generative adversarial network-based abnormality detection using only normal images for model training with application to digital breast tomosynthesis.

Scientific reports
Deep learning has shown tremendous potential in the task of object detection in images. However, a common challenge with this task is when only a limited number of images containing the object of interest are available. This is a particular issue in ...

Deep learning image reconstruction for pancreatic low-dose computed tomography: comparison with hybrid iterative reconstruction.

Abdominal radiology (New York)
PURPOSE: To evaluate image quality, image noise, and conspicuity of pancreatic ductal adenocarcinoma (PDAC) in pancreatic low-dose computed tomography (LDCT) reconstructed using deep learning image reconstruction (DLIR) and compare with those of imag...

Augmenting lung cancer diagnosis on chest radiographs: positioning artificial intelligence to improve radiologist performance.

Clinical radiology
AIM: To evaluate the role that artificial intelligence (AI) could play in assisting radiologists as the first reader of chest radiographs (CXRs), to increase the accuracy and efficiency of lung cancer diagnosis by flagging positive cases before passi...

Assistance from Automated ASPECTS Software Improves Reader Performance.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PURPOSE: To compare physicians' ability to read Alberta Stroke Program Early CT Score (ASPECTS) in patients with a large vessel occlusion within 6 hours of symptom onset when assisted by a machine learning-based automatic software tool, compared with...

Multiscale Attention Guided Network for COVID-19 Diagnosis Using Chest X-Ray Images.

IEEE journal of biomedical and health informatics
Coronavirus disease 2019 (COVID-19) is one of the most destructive pandemic after millennium, forcing the world to tackle a health crisis. Automated lung infections classification using chest X-ray (CXR) images could strengthen diagnostic capability ...

Feasibility of high-resolution magnetic resonance imaging of the liver using deep learning reconstruction based on the deep learning denoising technique.

Magnetic resonance imaging
PURPOSE: To evaluate the feasibility of High-resolution (HR) magnetic resonance imaging (MRI) of the liver using deep learning reconstruction (DLR) based on a deep learning denoising technique compared with standard-resolution (SR) imaging.