AIMC Topic: X-Rays

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COVID-19 Detection from Chest X-ray Images Using Feature Fusion and Deep Learning.

Sensors (Basel, Switzerland)
Currently, COVID-19 is considered to be the most dangerous and deadly disease for the human body caused by the novel coronavirus. In December 2019, the coronavirus spread rapidly around the world, thought to be originated from Wuhan in China and is r...

Deep learning-based X-ray inpainting for improving spinal 2D-3D registration.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Two-dimensional (2D)-3D registration is challenging in the presence of implant projections on intraoperative images, which can limit the registration capture range. Here, we investigate the use of deep-learning-based inpainting for removi...

Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy.

European radiology experimental
BACKGROUND: We aimed to train and test a deep learning classifier to support the diagnosis of coronavirus disease 2019 (COVID-19) using chest x-ray (CXR) on a cohort of subjects from two hospitals in Lombardy, Italy.

ADOPT: automatic deep learning and optimization-based approach for detection of novel coronavirus COVID-19 disease using X-ray images.

Journal of biomolecular structure & dynamics
In the hospital, because of the rise in cases daily, there are a small number of COVID-19 test kits available. For this purpose, a rapid alternative diagnostic choice to prevent COVID-19 spread among individuals must be implemented as an automatic de...

Artificial Intelligence-assisted chest X-ray assessment scheme for COVID-19.

European radiology
OBJECTIVES: To study whether a trained convolutional neural network (CNN) can be of assistance to radiologists in differentiating Coronavirus disease (COVID)-positive from COVID-negative patients using chest X-ray (CXR) through an ambispective clinic...

Ensemble learning based automatic detection of tuberculosis in chest X-ray images using hybrid feature descriptors.

Physical and engineering sciences in medicine
Tuberculosis (TB) remains one of the major health problems in modern times with a high mortality rate. While efforts are being made to make early diagnosis accessible and more reliable in high burden TB countries, digital chest radiography has become...

The Feature Ambiguity Mitigate Operator model helps improve bone fracture detection on X-ray radiograph.

Scientific reports
This study was performed to propose a method, the Feature Ambiguity Mitigate Operator (FAMO) model, to mitigate feature ambiguity in bone fracture detection on radiographs of various body parts. A total of 9040 radiographic studies were extracted. Th...

Automatic Lung Segmentation on Chest X-rays Using Self-Attention Deep Neural Network.

Sensors (Basel, Switzerland)
Accurate identification of the boundaries of organs or abnormal objects (e.g., tumors) in medical images is important in surgical planning and in the diagnosis and prognosis of diseases. In this study, we propose a deep learning-based method to segme...

A machine learning-based framework for diagnosis of COVID-19 from chest X-ray images.

Interdisciplinary sciences, computational life sciences
Corona virus disease (COVID-19) acknowledged as a pandemic by the WHO and mankind all over the world is vulnerable to this virus. Alternative tools are needed that can help in diagnosis of the coronavirus. Researchers of this article investigated the...