ArticleJournal of medical systems2015
Shape and texture based novel features for automated juxtapleural nodule detection in lung CTs.
Article in Journal of medical systems, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- Lung Nodule Detection from Feature Engineering to Deep Learning in Thoracic CT Images: a Comprehensive Review.Journal of digital imaging · 2020Pooled it
- Pulmonary nodule detection in low dose computed tomography using a medical-to-medical transfer learning approach.Journal of medical imaging (Bellingham, Wash.) · 2024Article
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- Hierarchical Voting-Based Feature Selection and Ensemble Learning Model Scheme for Glioma Grading with Clinical and Molecular Characteristics.International journal of molecular sciences · 2022Article
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- AI-Driven Image Analysis in Central Nervous System Tumors-Traditional Machine Learning, Deep Learning and Hybrid Models.Journal of biotechnology and biomedicine · 2022Article
- Rapid Assessment of Acute Ischemic Stroke by Computed Tomography Using Deep Convolutional Neural Networks.Journal of digital imaging · 2021Article
- Automatic Pulmonary Nodule Detection Applying Deep Learning or Machine Learning Algorithms to the LIDC-IDRI Database: A Systematic Review.Diagnostics (Basel, Switzerland) · 2019Review
- Expert knowledge-infused deep learning for automatic lung nodule detection.Journal of X-ray science and technology · 2019Article
- Multistage segmentation model and SVM-ensemble for precise lung nodule detection.International journal of computer assisted radiology and surgery · 2018Article
- Juxta-Vascular Pulmonary Nodule Segmentation in PET-CT Imaging Based on an LBF Active Contour Model with Information Entropy and Joint Vector.Computational and mathematical methods in medicine · 2018Article
- An Assisted Diagnosis System for Detection of Early Pulmonary Nodule in Computed Tomography Images.Journal of medical systems · 2017Article
- Correlation coefficient based supervised locally linear embedding for pulmonary nodule recognition.Computer methods and programs in biomedicine · 2016Article
- Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms: probing the Lung Image Database Consortium dataset with two statistical learning methods.Journal of medical imaging (Bellingham, Wash.) · 2016Article
- HOSVD-Based 3D Active Appearance Model: Segmentation of Lung Fields in CT Images.Journal of medical systems · 2016Article
- Computer-aided detection (CADe) and diagnosis (CADx) system for lung cancer with likelihood of malignancy.Biomedical engineering online · 2016Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer is one of the types of cancer with highest mortality rate in the world. In case of early detection and diagnosis, the survival rate of patients significantly increases. In this study, a novel method and system that provides automatic detection of juxtapleural nodule pattern have been developed from cross-sectional images of lung CT (Computerized Tomography). Shape-based and both shape and texture based 7 features are contributed to the literature for lung nodules. System that we developed consists of six main stages called preprocessing, lung segmentation, detection of nodule candidate regions, feature extraction, feature selection (with five feature ranking criteria) and classification. LIDC dataset containing cross-sectional images of lung CT has been utilized, 1410 nodule candidate regions and 40 features have been extracted from 138 cross-sectional images for 24 patients. Experimental results for 10 classifiers are obtained and presented. Adding our derived features to known 33 features has increased nodule recognition performance from 0.9639 to 0.9679 AUC value on generalized linear model regression (GLMR) for 22 selected features and being reached one of the most successful results in the literature.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.