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Treatment plan prediction for lung IMRT using deep learning based fluence map generation.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Recently, it has been shown that automated treatment planning can be executed by direct fluence prediction from patient anatomy using convolutional neural networks. Proof of principle publications utilise a fixed dose prescription and fixed ...

Emphysema Progression at CT by Deep Learning Predicts Functional Impairment and Mortality: Results from the COPDGene Study.

Radiology
Background Visual assessment remains the standard for evaluating emphysema at CT; however, it is time consuming, is subjective, requires training, and is affected by variability that may limit sensitivity to longitudinal change. Purpose To evaluate t...

WVALE: Weak variational autoencoder for localisation and enhancement of COVID-19 lung infections.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The COVID-19 pandemic is a major global health crisis of this century. The use of neural networks with CT imaging can potentially improve clinicians' efficiency in diagnosis. Previous studies in this field have primarily foc...

MEA-Net: multilayer edge attention network for medical image segmentation.

Scientific reports
Medical image segmentation is a fundamental step in medical analysis and diagnosis. In recent years, deep learning networks have been used for precise segmentation. Numerous improved encoder-decoder structures have been proposed for various segmentat...

Artificial Intelligence (AI) for Lung Nodules, From the Special Series on AI Applications.

AJR. American journal of roentgenology
Interest in artificial intelligence (AI) applications for lung nodules continues to grow among radiologists, particularly with the expanding eligibility criteria and clinical utilization of lung cancer screening CT. AI has been heavily investigated f...

An improved CNN-based architecture for automatic lung nodule classification.

Medical & biological engineering & computing
Lung cancer is one of the most critical diseases due to its significant death rate compared to all other types of cancer. The early diagnosis of lung cancer that improves the patient's chance of surviving is mostly done in two phases: screening throu...

Deep Learning-Based Classification of Reduced Lung Ultrasound Data From COVID-19 Patients.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
The application of lung ultrasound (LUS) imaging for the diagnosis of lung diseases has recently captured significant interest within the research community. With the ongoing COVID-19 pandemic, many efforts have been made to evaluate LUS data. A four...

Machine Learning for Cardiovascular Biomechanics Modeling: Challenges and Beyond.

Annals of biomedical engineering
Recent progress in machine learning (ML), together with advanced computational power, have provided new research opportunities in cardiovascular modeling. While classifying patient outcomes and medical image segmentation with ML have already shown si...