ArticleInternational journal of computer assisted radiology and surgery2016
A novel bone suppression method that improves lung nodule detection : Suppressing dedicated bone shadows in radiographs while preserving the remaining signal.
Article in International journal of computer assisted radiology and surgery, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 25 citations in OpenAlex.
- Interpretable Bayesian Modeling for Multireader Multicase Studies: Addressing Overdispersion and Limited Sample Size in Diagnostic Enhancement Evaluation.Statistics in medicine · 2026Article
- Efficient labeling for fine-tuning chest X-ray bone-suppression networks for pediatric patients.Medical physics · 2025Article
- Enhancing the target visibility with synthetic target specific digitally reconstructed radiograph for intrafraction motion monitoring: A proof-of-concept study.Medical physics · 2023Article
- Development of Debiasing Technique for Lung Nodule Chest X-ray Datasets to Generalize Deep Learning Models.Sensors (Basel, Switzerland) · 2023Article
- An Efficient and Robust Method for Chest X-ray Rib Suppression That Improves Pulmonary Abnormality Diagnosis.Diagnostics (Basel, Switzerland) · 2023Article
- Development and validation of bone-suppressed deep learning classification of COVID-19 presentation in chest radiographs.Quantitative imaging in medicine and surgery · 2022Article
- Improved detection of solitary pulmonary nodules on radiographs compared with deep bone suppression imaging.Quantitative imaging in medicine and surgery · 2021Article
- X-ray Dark-field Radiography - In-Vivo Diagnosis of Lung Cancer in Mice.Scientific reports · 2017Article
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeSuppressing thoracic bone shadows in chest radiographs has been previously reported to improve the detection rates for solid lung nodules, however at the cost of increased false detection rates. These bone suppression methods are based on an artificial neural network that was trained using dual-energy subtraction images in order to mimic their appearance.
methodHere, a novel approach is followed where all bone shadows crossing the lung field are suppressed sequentially leaving the intercostal space unaffected. Given a contour delineating a bone, its image region is spatially transferred to separate normal image gradient components from tangential component. Smoothing the normal partial gradient along the contour results in a reconstruction of the image representing the bone shadow only, because all other overlaid signals tend to cancel out each other in this representation.
resultsThe method works even with highly contrasted overlaid objects such as a pacemaker. The approach was validated in a reader study with two experienced chest radiologists, and these images helped improving both the sensitivity and the specificity of the readers for the detection and localization of solid lung nodules. The AUC improved significantly from 0.596 to 0.655 on a basis of 146 images from patients and normals with a total of 123 confirmed lung nodules.
conclusionSubtracting all reconstructed bone shadows from the original image results in a soft image where lung nodules are no longer obscured by bone shadows. Both the sensitivity and the specificity of experienced radiologists increased.
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