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Lung cancer identification: a review on detection and classification
Lung cancer is one of the most common diseases among humans and one of the major
causes of growing mortality. Medical experts believe that diagnosing lung cancer in the early …
causes of growing mortality. Medical experts believe that diagnosing lung cancer in the early …
An appraisal of lung nodules automatic classification algorithms for CT images
X Wang, K Mao, L Wang, P Yang, D Lu, P He - Sensors, 2019 - mdpi.com
Lung cancer is one of the most deadly diseases around the world representing about 26% of
all cancers in 2017. The five-year cure rate is only 18% despite great progress in recent …
all cancers in 2017. The five-year cure rate is only 18% despite great progress in recent …
Lung cancer histology classification from CT images based on radiomics and deep learning models
Adenocarcinoma (AC) and squamous cell carcinoma (SCC) are frequent reported cases of
non-small cell lung cancer (NSCLC), responsible for a large fraction of cancer deaths …
non-small cell lung cancer (NSCLC), responsible for a large fraction of cancer deaths …
Lung nodule classification via deep transfer learning in CT lung images
RVM Da Nóbrega, SA Peixoto… - 2018 IEEE 31st …, 2018 - ieeexplore.ieee.org
Lung cancer corresponds to 26% of all deaths due to cancer in 2017, accounting more than
1.5 million deaths globally. Considering this challenging situation, several computeraided …
1.5 million deaths globally. Considering this challenging situation, several computeraided …
Deep metric learning-based image retrieval system for chest radiograph and its clinical applications in COVID-19
In recent years, deep learning-based image analysis methods have been widely applied in
computer-aided detection, diagnosis and prognosis, and has shown its value during the …
computer-aided detection, diagnosis and prognosis, and has shown its value during the …
Object detection and classification: a joint selection and fusion strategy of deep convolutional neural network and SIFT point features
In the area of machine learning and pattern recognition, object classification is getting an
attraction due to its range of applications such as visual surveillance. In recent times …
attraction due to its range of applications such as visual surveillance. In recent times …
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 …
Small lung nodules detection based on local variance analysis and probabilistic neural network
Background and objective In medical examinations doctors use various techniques in order
to provide to the patients an accurate analysis of their actual state of health. One of the …
to provide to the patients an accurate analysis of their actual state of health. One of the …
RETRACTED ARTICLE: Lung nodule malignancy classification in chest computed tomography images using transfer learning and convolutional neural networks
RVM Da Nobrega, PP Reboucas Filho… - Neural Computing and …, 2020 - Springer
Lung cancer accounts for more than 1.5 million deaths worldwide, and it corresponded to
26% of all deaths due to cancer in 2017. However, lung computer-aided diagnosis systems …
26% of all deaths due to cancer in 2017. However, lung computer-aided diagnosis systems …
Multi-model ensemble learning architecture based on 3D CNN for lung nodule malignancy suspiciousness classification
H Liu, H Cao, E Song, G Ma, X Xu, R **, C Liu… - Journal of Digital …, 2020 - Springer
Classification of benign and malignant in lung nodules using chest CT images is a key step
in the diagnosis of early-stage lung cancer, as well as an effective way to improve the …
in the diagnosis of early-stage lung cancer, as well as an effective way to improve the …