Radiomics in breast cancer classification and prediction
Breast Cancer (BC) is the common form of cancer in women. Its diagnosis and screening are
usually performed through different imaging modalities such as mammography, magnetic …
usually performed through different imaging modalities such as mammography, magnetic …
Radiomics and deep learning in lung cancer
Lung malignancies have been extensively characterized through radiomics and deep
learning. By providing a three-dimensional characterization of the lesion, models based on …
learning. By providing a three-dimensional characterization of the lesion, models based on …
Perinodular and intranodular radiomic features on lung CT images distinguish adenocarcinomas from granulomas
Purpose To evaluate ability of radiomic (computer-extracted imaging) features to distinguish
non-small cell lung cancer adenocarcinomas from granulomas at noncontrast CT. Materials …
non-small cell lung cancer adenocarcinomas from granulomas at noncontrast CT. Materials …
Lungs cancer classification from CT images: An integrated design of contrast based classical features fusion and selection
Lung cancer is a fatal type of cancer and it causes of severe deaths of approximately 422
people every day, worldwide. However, an early diagnosis is an expedient requirement for …
people every day, worldwide. However, an early diagnosis is an expedient requirement for …
Artificial intelligence and radiomics in pulmonary nodule management: current status and future applications
Artificial intelligence (AI) has been present in some guise within the field of radiology for over
50 years. The first studies investigating computer-aided diagnosis in thoracic radiology date …
50 years. The first studies investigating computer-aided diagnosis in thoracic radiology date …
On the performance of lung nodule detection, segmentation and classification
Computed tomography (CT) screening is an effective way for early detection of lung cancer
in order to improve the survival rate of such a deadly disease. For more than two decades …
in order to improve the survival rate of such a deadly disease. For more than two decades …
Radiomics in lung diseases imaging: state-of-the-art for clinicians
Artificial intelligence (AI) has increasingly been serving the field of radiology over the last 50
years. As modern medicine is evolving towards precision medicine, offering personalized …
years. As modern medicine is evolving towards precision medicine, offering personalized …
Small lung nodules detection based on fuzzy-logic and probabilistic neural network with bioinspired reinforcement learning
Internal organs, like lungs, are very often examined by the use of screening methods. For
this purpose, we present an evaluation model based on a composition of fuzzy system …
this purpose, we present an evaluation model based on a composition of fuzzy system …
A wavelet features derived radiomics nomogram for prediction of malignant and benign early-stage lung nodules
R Jing, J Wang, J Li, X Wang, B Li, F Xue, G Shao… - Scientific reports, 2021 - nature.com
This study was to develop a radiomics nomogram mainly using wavelet features for
identifying malignant and benign early-stage lung nodules for high-risk screening. A total of …
identifying malignant and benign early-stage lung nodules for high-risk screening. A total of …
Machine learning and feature selection methods for disease classification with application to lung cancer screening image data
DAP Delzell, S Magnuson, T Peter, M Smith… - Frontiers in …, 2019 - frontiersin.org
As awareness of the habits and risks associated with lung cancer has increased, so has the
interest in promoting and improving upon lung cancer screening procedures. Recent …
interest in promoting and improving upon lung cancer screening procedures. Recent …