On the performance of lung nodule detection, segmentation and classification

Impact of Vessel Suppressed-CT on Diagnostic Accuracy in Detection of Pulmonary Metastasis and Reading Time

(2020) K. Martini et al.   ACADEMIC RADIOLOGY

An Embedded Multi-branch 3D Convolution Neural Network for False Positive Reduction in Lung Nodule Detection

(2020) Wangxia Zuo et al.   JOURNAL OF DIGITAL IMAGING

Homology‐based radiomic features for prediction of the prognosis of lung cancer based on CT‐based radiomics

(2020) Noriyuki Kadoya et al.   MEDICAL PHYSICS

Recurrent Attention Network for False Positive Reduction in the Detection of Pulmonary Nodules in Thoracic CT Scans

(2020) M. Mehdi Farhangi et al.   MEDICAL PHYSICS

External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodules

(2020) David R Baldwin et al.   THORAX

CT-Based Radiomic Signature as a Prognostic Factor in Stage IV ALK-Positive Non-small-cell Lung Cancer Treated With TKI Crizotinib: A Proof-of-Concept Study

(2020) Hailin Li et al.   Frontiers in Oncology

Radiomics: A primer for the radiation oncologist

(2020) J.-E. Bibault et al.   Cancer Radiotherapie

A Method of Rapid Quantification of Patient‐Specific Organ Doses for CT Using Deep‐Learning based Multi‐Organ Segmentation and GPU‐accelerated Monte Carlo Dose Computing

(2020) Zhao Peng et al.   MEDICAL PHYSICS

Classification of Lung Nodules Based on Deep Residual Networks and Migration Learning

(2020) Panpan Wu et al.   Computational Intelligence and Neuroscience

Comparison and Fusion of Deep Learning and Radiomics Features of Ground-Glass Nodules to Predict the Invasiveness Risk of Stage-I Lung Adenocarcinomas in CT Scan

(2020) Xianwu Xia et al.   Frontiers in Oncology

MD-NDNet: multi-dimension convolutional neural network for false positive reduction in pulmonary nodule detection

(2020) Zhan Wu et al.   PHYSICS IN MEDICINE AND BIOLOGY

Lesion-Harvester: Iteratively Mining Unlabeled Lesions and Hard-Negative Examples at Scale

(2020) Jinzheng Cai et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Improving Accuracy of Lung Nodule Classification Using Deep Learning with Focal Loss

(2019) Giang Son Tran et al.   Journal of Healthcare Engineering

External validation and recalibration of the Brock model to predict probability of cancer in pulmonary nodules using NLST data

(2019) Audrey Winter et al.   THORAX

Fast and Fully-Automated Detection and Segmentation of Pulmonary Nodules in Thoracic CT Scans Using Deep Convolutional Neural Networks

(2019) Xia Huang et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Prediction of pathologic stage in non-small cell lung cancer using machine learning algorithm based on CT image feature analysis

(2019) Lingming Yu et al.   BMC CANCER

Accuracy of the Vancouver Lung Cancer Risk Prediction Model Compared With That of Radiologists

(2019) Heber MacMahon et al.   CHEST

Machine learning approach for distinguishing malignant and benign lung nodules utilizing standardized perinodular parenchymal features from CT

(2019) Johanna Uthoff et al.   MEDICAL PHYSICS

Cancer treatment and survivorship statistics, 2019

(2019) Kimberly D. Miller et al.   CA-A CANCER JOURNAL FOR CLINICIANS

Multi-scale gradual integration CNN for false positive reduction in pulmonary nodule detection

(2019) Bum-Chae Kim et al.   NEURAL NETWORKS

A CAD system for pulmonary nodule prediction based on deep three-dimensional convolutional neural networks and ensemble learning

(2019) Wenkai Huang et al.   PLoS One

Can texture features improve the differentiation of infiltrative lung adenocarcinoma appearing as ground glass nodules in contrast-enhanced CT?

(2019) Chen Gao et al.   EUROPEAN JOURNAL OF RADIOLOGY

Application of artificial intelligence in the diagnosis of multiple primary lung cancer

(2019) Xin Li et al.   Thoracic Cancer

Multi-resolution convolutional networks for chest X-ray radiograph based lung nodule detection

(2019) Xuechen Li et al.   ARTIFICIAL INTELLIGENCE IN MEDICINE

Multi-level 3D Densenets for False-positive Reduction in Lung Nodule Detection Based on Chest Computed Tomography

(2019) Xiaoqi Lu et al.   Current Medical Imaging Reviews

Automatic classification of lung nodule candidates based on a novel 3D convolution network and knowledge transferred from a 2D network

(2019) Wangxia Zuo et al.   MEDICAL PHYSICS

A manifold learning regularization approach to enhance 3D CT image-based lung nodule classification

(2019) Ying Ren et al.   International Journal of Computer Assisted Radiology and Surgery

Distributed radiomics as a signature validation study using the Personal Health Train infrastructure

(2019) Zhenwei Shi et al.   Scientific Data

A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images

(2019) Jing Gong et al.   EUROPEAN RADIOLOGY

Multi-Task Deep Model With Margin Ranking Loss for Lung Nodule Analysis

(2019) Lihao Liu et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

MR-Forest: A Deep Decision Framework for False Positive Reduction in Pulmonary Nodule Detection

(2019) Hongbo Zhu et al.   IEEE Journal of Biomedical and Health Informatics

Automatic detection of multisize pulmonary nodules in CT images: Large-scale validation of the false-positive reduction step

(2018) Anindya Gupta et al.   MEDICAL PHYSICS

A deep 3D residual CNN for false-positive reduction in pulmonary nodule detection

(2018) Hongsheng Jin et al.   MEDICAL PHYSICS

Radiomic features analysis in computed tomography images of lung nodule classification

(2018) Chia-Hung Chen et al.   PLoS One

An Automatic Detection System of Lung Nodule Based on Multigroup Patch-Based Deep Learning Network

(2018) Hongyang Jiang et al.   IEEE Journal of Biomedical and Health Informatics

Automatic lung nodule detection using a 3D deep convolutional neural network combined with a multi-scale prediction strategy in chest CTs

(2018) Yu Gu et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Variable radiological lung nodule evaluation leads to divergent management recommendations

(2018) Arjun Nair et al.   EUROPEAN RESPIRATORY JOURNAL

Automated detection of lung cancer at ultralow dose PET/CT by deep neural networks – Initial results

(2018) Moritz Schwyzer et al.   LUNG CANCER

Pulmonary nodule segmentation with CT sample synthesis using adversarial networks

(2018) Yulei Qin et al.   MEDICAL PHYSICS

Predicting Malignancy Risk of Screen-Detected Lung Nodules–Mean Diameter or Volume

(2018) Martin Tammemagi et al.   Journal of Thoracic Oncology

Optimal deep learning model for classification of lung cancer on CT images

(2018) Lakshmanaprabu S.K. et al.   Future Generation Computer Systems-The International Journal of eScience

A Lightweight Multi-Section CNN for Lung Nodule Classification and Malignancy Estimation

(2018) Pranjal Sahu et al.   IEEE Journal of Biomedical and Health Informatics

Multilevel Contextual 3-D CNNs for False Positive Reduction in Pulmonary Nodule Detection

(2017) Qi Dou et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

(2017) Shaoqing Ren et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

A multi-kernel based framework for heterogeneous feature selection and over-sampling for computer-aided detection of pulmonary nodules

(2017) Peng Cao et al.   PATTERN RECOGNITION

Predicting survival time of lung cancer patients using radiomic analysis

(2017) Ahmad Chaddad et al.   Oncotarget

Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images

(2017) QingZeng Song et al.   Journal of Healthcare Engineering

Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier

(2016) Keming Mao et al.   Computational and Mathematical Methods in Medicine

Pulmonary Nodule Classification with Deep Convolutional Neural Networks on Computed Tomography Images

(2016) Wei Li et al.   Computational and Mathematical Methods in Medicine

An Assisted Diagnosis System for Detection of Early Pulmonary Nodule in Computed Tomography Images

(2016) Ji-kui Liu et al.   JOURNAL OF MEDICAL SYSTEMS

Ant Colony Optimization Approaches to Clustering of Lung Nodules from CT Images

(2014) Ravichandran C. Gopalakrishnan et al.   Computational and Mathematical Methods in Medicine

Refinement of lung nodule candidates based on local geometric shape analysis and Laplacian of Gaussian kernels

(2014) Soudeh Saien et al.   COMPUTERS IN BIOLOGY AND MEDICINE

An Intelligent System for Lung Cancer Diagnosis Using a New Genetic Algorithm Based Feature Selection Method

(2014) Chunhong Lu et al.   JOURNAL OF MEDICAL SYSTEMS

Automatic detection of solitary lung nodules using quality threshold clustering, genetic algorithm and diversity index

(2013) Antonio Oseas de Carvalho Filho et al.   ARTIFICIAL INTELLIGENCE IN MEDICINE

Ensemble-based hybrid probabilistic sampling for imbalanced data learning in lung nodule CAD

(2013) Peng Cao et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

A Hybrid Automatic System for the Diagnosis of Lung Cancer Based on Genetic Algorithm and Fuzzy Extreme Learning Machines

(2011) Mohammad Reza Daliri   JOURNAL OF MEDICAL SYSTEMS

Development and evaluation of a computer-aided diagnostic scheme for lung nodule detection in chest radiographs by means of two-stage nodule enhancement with support vector classification

(2011) Sheng Chen et al.   MEDICAL PHYSICS

Computer-aided diagnosis of pulmonary nodules using a two-step approach for feature selection and classifier ensemble construction

(2010) Michael C. Lee et al.   ARTIFICIAL INTELLIGENCE IN MEDICINE

Application of machine learning methodology for PET-based definition of lung cancer

(2010) A. Kerhet et al.   Current Oncology

A new computationally efficient CAD system for pulmonary nodule detection in CT imagery

(2010) Temesguen Messay et al.   MEDICAL IMAGE ANALYSIS

A novel fuzzy C-means algorithm for unsupervised heterogeneous tumor quantification in PET

(2010) Saoussen Belhassen et al.   MEDICAL PHYSICS

Segmentation of Lung Nodules in Computed Tomography Images Using Dynamic Programming and Multidirection Fusion Techniques1

(2009) Qian Wang et al.   ACADEMIC RADIOLOGY

Semi-automatic Volumetric Measurement of Lung Cancer Using Multi-detector CT

(2009) Shingo Iwano et al.   ACADEMIC RADIOLOGY

A Novel Approach to Nodule Feature Optimization on Thin Section Thoracic CT

(2009) Ravi Samala et al.   ACADEMIC RADIOLOGY

In Vivo Repeatability of Automated Volume Calculations of Small Pulmonary Nodules With CT

(2009) Cristiano Rampinelli et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

Shape-Based Computer-Aided Detection of Lung Nodules in Thoracic CT Images

(2009) Xujiong Ye et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

A large-scale evaluation of automatic pulmonary nodule detection in chest CT using local image features and k-nearest-neighbour classification

(2009) K. Murphy et al.   MEDICAL IMAGE ANALYSIS

Computer-aided detection for the identification of pulmonary nodules in pediatric oncology patients: initial experience

(2009) Emma J. Helm et al.   PEDIATRIC RADIOLOGY

A supervised ‘lesion-enhancement’ filter by use of a massive-training artificial neural network (MTANN) in computer-aided diagnosis (CAD)

(2009) Kenji Suzuki   PHYSICS IN MEDICINE AND BIOLOGY

Use of a Computer-aided Detection System to Detect Missed Lung Cancer at Chest Radiography

(2009) Charles S. White et al.   RADIOLOGY

Usefulness of Computer-Aided Diagnosis Schemes for Vertebral Fractures and Lung Nodules on Chest Radiographs

(2008) Satoshi Kasai et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

Computer-aided differentiation of malignant from benign solitary pulmonary nodules imaged by high-resolution CT

(2008) Shingo Iwano et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Lung nodule detection in low-dose and thin-slice computed tomography

(2008) A. Retico et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Segmentation of Pulmonary Nodules in Thoracic CT Scans: A Region Growing Approach

(2008) J. Dehmeshki et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING