Radiomics: the process and the challenges
“Radiomics” refers to the extraction and analysis of large amounts of advanced quantitative
imaging features with high throughput from medical images obtained with computed …
imaging features with high throughput from medical images obtained with computed …
The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans
SG Armato III, G McLennan, L Bidaut… - Medical …, 2011 - Wiley Online Library
Purpose: The development of computer‐aided diagnostic (CAD) methods for lung nodule
detection, classification, and quantitative assessment can be facilitated through a well …
detection, classification, and quantitative assessment can be facilitated through a well …
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 …
Integration of convolutional neural networks for pulmonary nodule malignancy assessment in a lung cancer classification pipeline
Abstract Background and Objective The early identification of malignant pulmonary nodules
is critical for a better lung cancer prognosis and less invasive chemo or radio therapies …
is critical for a better lung cancer prognosis and less invasive chemo or radio therapies …
Identification of breast malignancy by marker-controlled watershed transformation and hybrid feature set for healthcare
Breast cancer is a highly prevalent disease in females that may lead to mortality in severe
cases. The mortality can be subsided if breast cancer is diagnosed at an early stage. The …
cases. The mortality can be subsided if breast cancer is diagnosed at an early stage. The …
Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms: probing the Lung Image Database …
MC Hancock, JF Magnan - Journal of Medical Imaging, 2016 - spiedigitallibrary.org
In the assessment of nodules in CT scans of the lungs, a number of image-derived features
are diagnostically relevant. Currently, many of these features are defined only qualitatively …
are diagnostically relevant. Currently, many of these features are defined only qualitatively …
Lung nodule detection algorithm based on rank correlation causal structure learning
J Yang, L Jiang, K Xie, Q Chen, A Wang - Expert Systems with Applications, 2023 - Elsevier
Early diagnosis can significantly improve the survival rate of lung cancer patients. This study
attempts to construct a causal structure network between the computational and semantic …
attempts to construct a causal structure network between the computational and semantic …
A texture feature analysis for diagnosis of pulmonary nodules using LIDC-IDRI database
This paper evaluated the performance of two-dimensional (2D) and 3D texture features from
CT images on pulmonary nodules diagnosis using the large database LIDC-IDRI. Total of …
CT images on pulmonary nodules diagnosis using the large database LIDC-IDRI. Total of …
Improved pulmonary nodule classification utilizing quantitative lung parenchyma features
SKN Dilger, J Uthoff, A Judisch… - Journal of Medical …, 2015 - spiedigitallibrary.org
Current computer-aided diagnosis (CAD) models for determining pulmonary nodule
malignancy characterize nodule shape, density, and border in computed tomography (CT) …
malignancy characterize nodule shape, density, and border in computed tomography (CT) …
[HTML][HTML] A weighted rule based method for predicting malignancy of pulmonary nodules by nodule characteristics
Predicting malignancy of solitary pulmonary nodules from computer tomography scans is a
difficult and important problem in the diagnosis of lung cancer. This paper investigates the …
difficult and important problem in the diagnosis of lung cancer. This paper investigates the …