AIMC Topic: X-Rays

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Semisolid Pharmaceutical Product Characterization Using Non-invasive X-ray Microscopy and AI-Based Image Analytics.

The AAPS journal
This work reports the use of X-ray microscopy (XRM) imaging to characterize the microstructure of semisolid formulations containing multiple immiscible phases. For emulsion-based semisolid formulations, the disperse phase globule size and its distrib...

Learning-based occupational x-ray scatter estimation.

Physics in medicine and biology
During x-ray-guided interventional procedures, the medical staff is exposed to scattered ionizing radiation caused by the patient. To increase the staff's awareness of the invisible radiation and monitor dose online, computational scatter estimation ...

Deep learning-based 2D/3D registration of an atlas to biplanar X-ray images.

International journal of computer assisted radiology and surgery
PURPOSE: The registration of a 3D atlas image to 2D radiographs enables 3D pre-operative planning without the need to acquire costly and high-dose CT-scans. Recently, many deep-learning-based 2D/3D registration methods have been proposed which tackle...

A radiomics-boosted deep-learning model for COVID-19 and non-COVID-19 pneumonia classification using chest x-ray images.

Medical physics
PURPOSE: To develop a deep learning model design that integrates radiomics analysis for enhanced performance of COVID-19 and non-COVID-19 pneumonia detection using chest x-ray images.

Deep Learning-Based Computer-Aided Pneumothorax Detection Using Chest X-ray Images.

Sensors (Basel, Switzerland)
Pneumothorax is a thoracic disease leading to failure of the respiratory system, cardiac arrest, or in extreme cases, death. Chest X-ray (CXR) imaging is the primary diagnostic imaging technique for the diagnosis of pneumothorax. A computerized diagn...

Deep Supervised Domain Adaptation for Pneumonia Diagnosis From Chest X-Ray Images.

IEEE journal of biomedical and health informatics
Pneumonia is one of the most common treatable causes of death, and early diagnosis allows for early intervention. Automated diagnosis of pneumonia can therefore improve outcomes. However, it is challenging to develop high-performance deep learning mo...

INASNET: Automatic identification of coronavirus disease (COVID-19) based on chest X-ray using deep neural network.

ISA transactions
Testing is one of the important methodologies used by various countries in order to fight against COVID-19 infection. The infection is considered as one of the deadliest ones although the mortality rate is not very high. COVID-19 infection is being c...

COVID-19 Identification System Using Transfer Learning Technique With Mobile-NetV2 and Chest X-Ray Images.

Frontiers in public health
Diagnosis is a crucial precautionary step in research studies of the coronavirus disease, which shows indications similar to those of various pneumonia types. The COVID-19 pandemic has caused a significant outbreak in more than 150 nations and has si...

Automated pneumothorax triaging in chest X-rays in the New Zealand population using deep-learning algorithms.

Journal of medical imaging and radiation oncology
INTRODUCTION: The primary aim was to develop convolutional neural network (CNN)-based artificial intelligence (AI) models for pneumothorax classification and segmentation for automated chest X-ray (CXR) triaging. A secondary aim was to perform interp...

Caries segmentation on tooth X-ray images with a deep network.

Journal of dentistry
OBJECTIVES: Deep learning has been a promising technology in many biomedical applications. In this study, a deep network was proposed aiming for caries segmentation on the clinically collected tooth X-ray images.