AIMC Topic: Lung

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Lung_PAYNet: a pyramidal attention based deep learning network for lung nodule segmentation.

Scientific reports Nov 25, 2022
Accurate and reliable lung nodule segmentation in computed tomography (CT) images is required for early diagnosis of lung cancer. Some of the difficulties in detecting lung nodules include the various types and shapes of lung nodules, lung nodules ne...
Neural Networks, Computer Tomography, X-Ray Computed Lung Deep Learning Thorax
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Development and performance evaluation of a deep learning lung nodule detection system.

BMC medical imaging Nov 22, 2022
BACKGROUND: Lung cancer is the leading cause of cancer-related deaths throughout the world. Chest computed tomography (CT) is now widely used in the screening and diagnosis of lung cancer due to its effectiveness. Radiologists must identify each smal...
Phantoms, Imaging Deep Learning Lung Neoplasms Tomography, X-Ray Computed Lung Humans
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Deep learning-based dynamic PET parametric K image generation from lung static PET.

European radiology Nov 18, 2022
OBJECTIVES: PET/CT is a first-line tool for the diagnosis of lung cancer. The accuracy of quantification may suffer from various factors throughout the acquisition process. The dynamic PET parametric K provides better quantification and improve speci...
Positron Emission Tomography Computed Tomography Positron-Emission Tomography Image Processing, Computer-Assisted Lung Neoplasms Humans Lung Deep Learning
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Multi-Perspective Hierarchical Deep-Fusion Learning Framework for Lung Nodule Classification.

Sensors (Basel, Switzerland) Nov 18, 2022
Lung cancer is the leading cancer type that causes mortality in both men and women. Computer-aided detection (CAD) and diagnosis systems can play a very important role for helping physicians with cancer treatments. This study proposes a hierarchical ...
Lung Deep Learning Radiographic Image Interpretation, Computer-Assisted Solitary Pulmonary Nodule Tomography, X-Ray Computed Humans Female
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A Dual-Channel Deep Learning Approach for Lung Cavity Estimation From Hyperpolarized Gas and Proton MRI.

Journal of magnetic resonance imaging : JMRI Nov 14, 2022
BACKGROUND: Hyperpolarized gas MRI can quantify regional lung ventilation via biomarkers, including the ventilation defect percentage (VDP). VDP is computed from segmentations derived from spatially co-registered functional hyperpolarized gas and str...
Retrospective Studies Female Male Humans Biomarkers Magnetic Resonance Imaging Protons Lung Deep Learning
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Editorial for "A Dual-Channel Deep Learning Approach for Lung Cavity Estimation From Hyperpolarized Gas and Proton MRI".

Journal of magnetic resonance imaging : JMRI Nov 7, 2022
Humans Lung Protons Xenon Isotopes Helium Deep Learning Magnetic Resonance Imaging
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A Fissure-Aided Registration Approach for Automatic Pulmonary Lobe Segmentation Using Deep Learning.

Sensors (Basel, Switzerland) Nov 7, 2022
The segmentation of pulmonary lobes is important in clinical assessment, lesion location, and surgical planning. Automatic lobe segmentation is challenging, mainly due to the incomplete fissures or the morphological variation resulting from lung dise...
Image Processing, Computer-Assisted Lung Diseases Humans Algorithms Lung Deep Learning Tomography, X-Ray Computed
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Lesion detection of chest X-Ray based on scalable attention residual CNN.

Mathematical biosciences and engineering : MBE Nov 4, 2022
Most of the research on disease recognition in chest X-rays is limited to segmentation and classification, but the problem of inaccurate recognition in edges and small parts makes doctors spend more time making judgments. In this paper, we propose a ...
Radiography, Thoracic X-Rays Algorithms Lung Neural Networks, Computer
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Imaging to Explore the Interface between Pulmonary Structure and Function.

Radiology Oct 25, 2022
Diagnostic Imaging Lung Volume Measurements Deep Learning Idiopathic Pulmonary Fibrosis Humans Lung
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Deep Learning for Estimating Lung Capacity on Chest Radiographs Predicts Survival in Idiopathic Pulmonary Fibrosis.

Radiology Oct 25, 2022
Background Total lung capacity (TLC) has been estimated with use of chest radiographs based on time-consuming methods, such as planimetric techniques and manual measurements. Purpose To develop a deep learning-based, multidimensional model capable of...
Middle Aged Humans Deep Learning Lung Retrospective Studies Aged Idiopathic Pulmonary Fibrosis Radiography Male Lung Volume Measurements
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