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Solitary Pulmonary Nodule

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Impact of deep learning image reconstruction on volumetric accuracy and image quality of pulmonary nodules with different morphologies in low-dose CT.

Cancer imaging : the official publication of the International Cancer Imaging Society May 9, 2024
BACKGROUND: This study systematically compares the impact of innovative deep learning image reconstruction (DLIR, TrueFidelity) to conventionally used iterative reconstruction (IR) on nodule volumetry and subjective image quality (IQ) at highly reduc...
Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Humans Phantoms, Imaging Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted
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Development and external validation of a multimodal integrated feature neural network (MIFNN) for the diagnosis of malignancy in small pulmonary nodules (≤10 mm).

Biomedical physics & engineering express May 8, 2024
. Current lung cancer screening protocols primarily evaluate pulmonary nodules, yet often neglect the malignancy risk associated with small nodules (≤10 mm). This study endeavors to optimize the management of pulmonary nodules in this population by d...
Tomography, X-Ray Computed Female Reproducibility of Results Aged Neural Networks, Computer Algorithms Humans Retrospective Studies Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Early Detection of Cancer Male Middle Aged Deep Learning China
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Clinical value of deep learning image reconstruction on the diagnosis of pulmonary nodule for ultra-low-dose chest CT imaging.

Clinical radiology Apr 20, 2024
PURPOSE: To compare the image quality and pulmonary nodule detectability between deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-Veo (ASIR-V) in ultra-low-dose CT (ULD-CT).
Humans Prospective Studies Tomography, X-Ray Computed Female Deep Learning Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Aged Adult Male Middle Aged Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Signal-To-Noise Ratio
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Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation.

European radiology Mar 27, 2024
OBJECTIVE: To investigate the effect of uncertainty estimation on the performance of a Deep Learning (DL) algorithm for estimating malignancy risk of pulmonary nodules.
Risk Assessment Deep Learning Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Uncertainty Female Aged Male Middle Aged Humans Algorithms Retrospective Studies Tomography, X-Ray Computed
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Robust deep learning from incomplete annotation for accurate lung nodule detection.

Computers in biology and medicine Mar 26, 2024
Deep learning plays a significant role in the detection of pulmonary nodules in low-dose computed tomography (LDCT) scans, contributing to the diagnosis and treatment of lung cancer. Nevertheless, its effectiveness often relies on the availability of...
Lung Neoplasms Humans Lung Solitary Pulmonary Nodule Deep Learning Radiographic Image Interpretation, Computer-Assisted
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Enhancing Lung Nodule Classification: A Novel CViEBi-CBGWO Approach with Integrated Image Preprocessing.

Journal of imaging informatics in medicine Mar 25, 2024
Cancer detection and accurate classification pose significant challenges for medical professionals, as it is described as a lethal illness. Diagnosing the malignant lung nodules in its initial stage significantly enhances the recovery and survival ra...
Solitary Pulmonary Nodule Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Lung Humans Image Processing, Computer-Assisted Neural Networks, Computer Lung Neoplasms Algorithms
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Socio-Economic Factors and Clinical Context Can Predict Adherence to Incidental Pulmonary Nodule Follow-up via Machine Learning Models.

Journal of the American College of Radiology : JACR Mar 8, 2024
OBJECTIVE: To quantify the relative importance of demographic, contextual, socio-economic, and nodule-related factors that influence patient adherence to incidental pulmonary nodule (IPN) follow-up visits and evaluate the predictive performance of ma...
Humans Machine Learning Solitary Pulmonary Nodule Middle Aged Female Patient Compliance Lung Neoplasms Aged Incidental Findings Socioeconomic Factors Adult Male
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LGDNet: local feature coupling global representations network for pulmonary nodules detection.

Medical & biological engineering & computing Mar 2, 2024
Detection of suspicious pulmonary nodules from lung CT scans is a crucial task in computer-aided diagnosis (CAD) systems. In recent years, various deep learning-based approaches have been proposed and demonstrated significant potential for addressing...
Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Algorithms Tomography, X-Ray Computed Lung Diagnosis, Computer-Assisted Deep Learning Lung Neoplasms Humans
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Improving Image Quality and Nodule Characterization in Ultra-low-dose Lung CT with Deep Learning Image Reconstruction.

Academic radiology Feb 29, 2024
RATIONALE AND OBJECTIVE: To investigate the influence of the deep learning image reconstruction (DLIR) on the image quality and quantitative analysis of pulmonary nodules under ultra-low dose lung CT conditions.
Middle Aged Deep Learning Multiple Pulmonary Nodules Lung Neoplasms Humans Female Solitary Pulmonary Nodule Aged Prospective Studies Adult Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Male Radiation Dosage
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Overcoming the Challenge of Accurate Segmentation of Lung Nodules: A Multi-crop CNN Approach.

Journal of imaging informatics in medicine Feb 12, 2024
Lung nodules are generated based on the growth of small and round- or oval-shaped cells in the lung, which are either cancerous or non-cancerous. Accurate segmentation of these nodules is crucial for early detection and diagnosis of lung cancer. Howe...
Tomography, X-Ray Computed Lung Lung Neoplasms Solitary Pulmonary Nodule Humans Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted Algorithms
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