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Computer‐aided diagnosis systems for lung cancer: challenges and methodologies
This paper overviews one of the most important, interesting, and challenging problems in
oncology, the problem of lung cancer diagnosis. Develo** an effective computer-aided …
oncology, the problem of lung cancer diagnosis. Develo** an effective computer-aided …
Deeplung: Deep 3d dual path nets for automated pulmonary nodule detection and classification
In this work, we present a fully automated lung computed tomography (CT) cancer diagnosis
system, DeepLung. DeepLung consists of two components, nodule detection (identifying the …
system, DeepLung. DeepLung consists of two components, nodule detection (identifying the …
Multi-scale convolutional neural networks for lung nodule classification
We investigate the problem of diagnostic lung nodule classification using thoracic Computed
Tomography (CT) screening. Unlike traditional studies primarily relying on nodule …
Tomography (CT) screening. Unlike traditional studies primarily relying on nodule …
Alzheimer's disease diagnostics by adaptation of 3D convolutional network
Early diagnosis, playing an important role in preventing progress and treating the
Alzheimer's disease (AD), is based on classification of features extracted from brain images …
Alzheimer's disease (AD), is based on classification of features extracted from brain images …
SANet: A slice-aware network for pulmonary nodule detection
Lung cancer is the most common cause of cancer death worldwide. A timely diagnosis of the
pulmonary nodules makes it possible to detect lung cancer in the early stage, and thoracic …
pulmonary nodules makes it possible to detect lung cancer in the early stage, and thoracic …
Lung and pancreatic tumor characterization in the deep learning era: novel supervised and unsupervised learning approaches
Risk stratification (characterization) of tumors from radiology images can be more accurate
and faster with computer-aided diagnosis (CAD) tools. Tumor characterization through such …
and faster with computer-aided diagnosis (CAD) tools. Tumor characterization through such …
Texture feature analysis for computer-aided diagnosis on pulmonary nodules
Differentiation of malignant and benign pulmonary nodules is of paramount clinical
importance. Texture features of pulmonary nodules in CT images reflect a powerful …
importance. Texture features of pulmonary nodules in CT images reflect a powerful …
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 …
Risk stratification of lung nodules using 3D CNN-based multi-task learning
Risk stratification of lung nodules is a task of primary importance in lung cancer diagnosis.
Any improvement in robust and accurate nodule characterization can assist in identifying …
Any improvement in robust and accurate nodule characterization can assist in identifying …
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 …