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Lung

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Artificial intelligence in computed tomography for quantifying lung changes in the era of CFTR modulators.

The European respiratory journal
BACKGROUND: Chest computed tomography (CT) remains the imaging standard for demonstrating cystic fibrosis (CF) airway structural disease . However, visual scoring systems as an outcome measure are time consuming, require training and lack high reprod...

Segmentation of CT Lung Images Using FCM with Active Contour and CNN Classifier.

Asian Pacific journal of cancer prevention : APJCP
OBJECTIVE: Lung cancer is one of the unsafe diseases for human which reduces the patient life time. Generally, most of the lung cancers are identified after it has been spread into the lung parts and moreover it is difficult to find the lung cancer a...

Proposing a novel deep network for detecting COVID-19 based on chest images.

Scientific reports
The rapid outbreak of coronavirus threatens humans' life all around the world. Due to the insufficient diagnostic infrastructures, developing an accurate, efficient, inexpensive, and quick diagnostic tool is of great importance. To date, researchers ...

Cascaded 3D UNet architecture for segmenting the COVID-19 infection from lung CT volume.

Scientific reports
World Health Organization (WHO) declared COVID-19 (COronaVIrus Disease 2019) as pandemic on March 11, 2020. Ever since then, the virus is undergoing different mutations, with a high rate of dissemination. The diagnosis and prognosis of COVID-19 are c...

Deep learning driven predictive treatment planning for adaptive radiotherapy of lung cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: To develop a novel deep learning algorithm of sequential analysis, Seq2Seq, for predicting weekly anatomical changes of lung tumor and esophagus during definitive radiotherapy, incorporate the potential tumor shrinkage into a ...

COPD identification and grading based on deep learning of lung parenchyma and bronchial wall in chest CT images.

The British journal of radiology
OBJECTIVE: Chest CT can display the main pathogenic factors of chronic obstructive pulmonary disease (COPD), emphysema and airway wall remodeling. This study aims to establish deep convolutional neural network (CNN) models using these two imaging mar...

Automatic contouring of normal tissues with deep learning for preclinical radiation studies.

Physics in medicine and biology
Delineation of relevant normal tissues is a bottleneck in image-guided precision radiotherapy workflows for small animals. A deep learning (DL) model for automatic contouring using standardized 3D micro cone-beam CT (CBCT) volumes as input is propose...

Classification of subtypes including LCNEC in lung cancer biopsy slides using convolutional neural network from scratch.

Scientific reports
Identifying the lung carcinoma subtype in small biopsy specimens is an important part of determining a suitable treatment plan but is often challenging without the help of special and/or immunohistochemical stains. Pathology image analysis that tackl...

A Machine-Learning Model for Lung Age Forecasting by Analyzing Exhalations.

Sensors (Basel, Switzerland)
Spirometers are important devices for following up patients with respiratory diseases. These are mainly located only at hospitals, with all the disadvantages that this can entail. This limits their use and consequently, the supervision of patients. R...

Novel-view X-ray projection synthesis through geometry-integrated deep learning.

Medical image analysis
X-ray imaging is a widely used approach to view the internal structure of a subject for clinical diagnosis, image-guided interventions and decision-making. The X-ray projections acquired at different view angles provide complementary information of p...