AIMC Topic: Lung Neoplasms
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Spiculation Sign Recognition in a Pulmonary Nodule Based on Spiking Neural P Systems.
BioMed research international
Dec 23, 2020
The spiculation sign is one of the main signs to distinguish benign and malignant pulmonary nodules. In order to effectively extract the image feature of a pulmonary nodule for the spiculation sign distinguishment, a new spiculation sign recognition ...
On the robustness of deep learning-based lung-nodule classification for CT images with respect to image noise.
Physics in medicine and biology
Dec 22, 2020
Robustness is an important aspect when evaluating a method of medical image analysis. In this study, we investigated the robustness of a deep learning (DL)-based lung-nodule classification model for CT images with respect to noise perturbations. A de...
Deep learning-based real-time volumetric imaging for lung stereotactic body radiation therapy: a proof of concept study.
Physics in medicine and biology
Dec 18, 2020
Due to the inter- and intra- variation of respiratory motion, it is highly desired to provide real-time volumetric images during the treatment delivery of lung stereotactic body radiation therapy (SBRT) for accurate and active motion management. In t...
A physics-guided modular deep-learning based automated framework for tumor segmentation in PET.
Physics in medicine and biology
Dec 18, 2020
An important need exists for reliable positron emission tomography (PET) tumor-segmentation methods for tasks such as PET-based radiation-therapy planning and reliable quantification of volumetric and radiomic features. To address this need, we propo...
Denoising Autoencoder, A Deep Learning Algorithm, Aids the Identification of A Novel Molecular Signature of Lung Adenocarcinoma.
Genomics, proteomics & bioinformatics
Dec 18, 2020
Precise biomarker development is a key step in disease management. However, most of the published biomarkers were derived from a relatively small number of samples with supervised approaches. Recent advances in unsupervised machine learning promise t...
NSCR-Based DenseNet for Lung Tumor Recognition Using Chest CT Image.
BioMed research international
Dec 16, 2020
Nonnegative sparse representation has become a popular methodology in medical analysis and diagnosis in recent years. In order to resolve network degradation, higher dimensionality in feature extraction, data redundancy, and other issues faced when m...
3D deep learning based classification of pulmonary ground glass opacity nodules with automatic segmentation.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Dec 11, 2020
Classifying ground-glass lung nodules (GGNs) into atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) on diagnostic CT images is important to evaluate the th...
Predicting potential residues associated with lung cancer using deep neural network.
Mutation research
Dec 11, 2020
Lung cancer is a prominent type of cancer, which leads to high mortality rate worldwide. The major lung cancers lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) occur mainly due to somatic driver mutations in proteins and screening of su...
Artificial intelligence-based imaging analytics and lung cancer diagnostics: Considerations for health system leaders.
Healthcare management forum
Dec 10, 2020
Lung cancer is a leading cause of cancer death in Canada, and accurate, early diagnosis are critical to improving clinical outcomes. Artificial Intelligence (AI)-based imaging analytics are a promising healthcare innovation that aim to improve the ac...
Immune profile of the tumor microenvironment and the identification of a four-gene signature for lung adenocarcinoma.
Aging
Dec 9, 2020
The composition and relative abundances of immune cells in the tumor microenvironment are key factors affecting the progression of lung adenocarcinomas (LUADs) and the efficacy of immunotherapy. Using the cancer gene expression dataset from The Cance...
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