ArticlePattern recognition2013
Automated Delineation of Lung Tumors from CT Images Using a Single Click Ensemble Segmentation Approach.
Article in Pattern recognition, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed.
- Revealing Tumor Habitats from Texture Heterogeneity Analysis for Classification of Lung Cancer Malignancy and Aggressiveness.Scientific reports · 2019Trial
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- Preoperative CT-Based Habitat Radiomics Classifiers Predict Recurrence in Non-Small Cell Lung Cancer.medRxiv : the preprint server for health sciences · 2026Article
- Utilizing Clinicopathological and Radiomic Features for Risk Stratification of Lung Cancer Recurrence.Academic radiology · 2025Article
- Radiomics: Assessing Significance and Correlation with Ground-Truth Data in Precision Medicine in Lung Adenocarcinoma.Bioengineering (Basel, Switzerland) · 2025Article
- Evaluating clinical and radiomic features for predicting lung cancer recurrence pre- and post-tumor resection.Proceedings of SPIE--the International Society for Optical Engineering · 2024Article
- Application of Machine Learning and Deep Learning Techniques for COVID-19 Screening Using Radiological Imaging: A Comprehensive Review.SN computer science · 2023Article
- An Automatic Segmentation Method for Lung Tumor Based on Improved Region Growing Algorithm.Diagnostics (Basel, Switzerland) · 2022Article
- Radiomics in medical imaging: pitfalls and challenges in clinical management.Japanese journal of radiology · 2022Review
- EGFR Mutation Status and Subtypes Predicted by CT-Based 3D Radiomic Features in Lung Adenocarcinoma.OncoTargets and therapy · 2022Article
- Article
- A transfer learning based deep learning model to diagnose covid-19 CT scan images.Health and technology · 2022Article
- The value of asphericity derived from T1-weighted MR in differentiating intraparenchymal ring-enhancing lesions-comparison of glioblastomas and brain abscesses.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2021Article
- Lung tumor segmentation in 4D CT images using motion convolutional neural networks.Medical physics · 2021Article
- Automatic COVID-19 lung infected region segmentation and measurement using CT-scans images.Pattern recognition · 2021Article
- Mouse lung automated segmentation tool for quantifying lung tumors after micro-computed tomography.PloS one · 2021Article
- Water Cycle Bat Algorithm and Dictionary-Based Deformable Model for Lung Tumor Segmentation.International journal of biomedical imaging · 2021Article
- Stability and reproducibility of computed tomography radiomic features extracted from peritumoral regions of lung cancer lesions.Medical physics · 2019Article
- Automatic glioma segmentation based on adaptive superpixel.BMC medical imaging · 2019Article
- Quantitative Imaging features Improve Discrimination of Malignancy in Pulmonary nodules.Scientific reports · 2019Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
A single click ensemble segmentation (SCES) approach based on an existing "Click&Grow" algorithm is presented. The SCES approach requires only one operator selected seed point as compared with multiple operator inputs, which are typically needed. This facilitates processing large numbers of cases. Evaluation on a set of 129 CT lung tumor images using a similarity index (SI) was done. The average SI is above 93% using 20 different start seeds, showing stability. The average SI for 2 different readers was
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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.