Lung Nodule Detection
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Benchmarks
LIDC-IDRI
LUNA2016 FPRED
Most implemented
Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis
DeepSEED: 3D Squeeze-and-Excitation Encoder-Decoder Convolutional Neural Networks for Pulmonary Nodule Detection
DeepEM: Deep 3D ConvNets With EM For Weakly Supervised Pulmonary Nodule Detection
Papers
Can Unsupervised Methods Outperform Supervised Deep Learning When Ground Truth Is Sparse? A Case Study of Bronchovascular Bundle Segmentation in Low-Dose CT
Background Lung cancer remains the deadliest cancer worldwide because it is often diagnosed too late. Effective treatment depends on detection at an early screening stage. However, the growing number of patients and the …
Lung Nodule DetectionNoduLoCC2026: Lung Nodule Localization and Classification Contest from Chest X-Ray Images
We propose NoduLoCC2026, a challenge on lung nodule detection and localization in chest X-ray images. We have provided a dataset for both tasks and received submissions from 5 international teams. The participating teams…
Lung Nodule DetectionReconstruction Interval Z-Phase Dependence of AI Detection Sensitivity in CT Lung Nodule Screening
Background: Sensitivity of AI-assisted lung nodule detection systems is known to vary with CT acquisition parameters including radiation dose, reconstruction kernel, and slice thickness. However, the dependence of detect…
Lung Nodule DetectionBeyond Benchmarks: A Framework for Post Deployment Validation of CT Lung Nodule Detection AI
Background: Artificial intelligence (AI) assisted lung nodule detection systems are increasingly deployed in clinical settings without site-specific validation. Performance reported under benchmark conditions may not ref…
Lung Nodule DetectionA Diffusion-Driven Fine-Grained Nodule Synthesis Framework for Enhanced Lung Nodule Detection from Chest Radiographs
Early detection of lung cancer in chest radiographs (CXRs) is crucial for improving patient outcomes, yet nodule detection remains challenging due to their subtle appearance and variability in radiological characteristic…
Synthetic Data GenerationLung Nodule DetectionLung nodule classification on CT scan patches using 3D convolutional neural networks
Lung cancer remains one of the most common and deadliest forms of cancer worldwide. The likelihood of successful treatment depends strongly on the stage at which the disease is diagnosed. Therefore, early detection of lu…
Lung Nodule ClassificationLung Nodule Detection