AIMC Topic: Lung

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Hybrid intelligence in medical image segmentation.

Scientific reports
Medical image segmentation is vital for precise identification and analysis of anatomical structures and pathological regions, yet traditional models often fall short in aligning with clinical workflows, requiring extensive manual correction even whe...

A Custom Annotated Dataset for Segmentation of Pulmonary Veins, Arteries, and Airways.

Scientific data
Accurate segmentation of pulmonary structures from computed tomography (CT) is critical for lung disease management, yet progress is hampered by a lack of large-scale, public datasets with comprehensive multi-structure annotations. To address this, w...

Impact of patient-specific deep learning lung organs-at-risk segmentation on accumulated dose in online adaptive 0.35 T MR-guided radiotherapy.

Physics in medicine and biology
Online adaptation in magnetic resonance imaging-guided radiotherapy (MRgRT) for lung cancer is hindered by time-consuming organs-at-risk (OARs) recontouring on daily MR images (dMRIs) and inter-/intra-observer variability. Deep learning auto-segmenta...

Long-range correlation-guided dual-encoder fusion network for medical images.

Scientific reports
Multimodal medical image fusion plays an important role in clinical applications. However, multimodal medical image fusion methods ignore the feature dependence among modals, and the feature fusion ability with different granularity is not strong. A ...

New lung ultrasound system for rapid triage of pulmonary disease without a radiologist or sonographer.

BMC pulmonary medicine
BACKGROUND: Most people in the world lack access to medical imaging including for assessment of pulmonary disease. We sought to improve access to pulmonary imaging by developing a rapid automated system for triage of pulmonary disease using lung ultr...

Common genetic variation influencing the human lung imaging phenotypes.

Nature communications
Lung structures are critical for gas exchange and contribute to the pathogenesis of respiratory diseases, exhibiting notable lobe-specific heterogeneity. To investigate their genetic basis, we apply a deep-learning AI system and Pyradiomics to define...

Metagenomic next-generation sequencing unraveled the characteristic of lung microbiota in patients with checkpoint inhibitor pneumonitis: results from a prospective cohort study.

Journal for immunotherapy of cancer
BACKGROUND: Checkpoint inhibitor pneumonitis (CIP) is among the most lethal immune-related adverse events in patients with cancer receiving immunotherapy. This study aims to characterize the lung microbiome in patients with CIP and evaluate its diagn...

AI-based HRCT quantification reveals DLCO and TLC as key determinants of ILD severity in connective tissue diseases.

RMD open
OBJECTIVE: Interstitial lung disease (ILD) represents the most common and severe organ manifestation observed in patients diagnosed with connective tissue diseases (CTDs). The aim of this retrospective cross-sectional study was to identify clinical r...

A semi-automated algorithm for image analysis of respiratory organoids.

PLoS computational biology
Respiratory organoids have emerged as a powerful in vitro model for studying respiratory diseases and drug discovery. However, the high-throughput analysis of organoid images remains a challenge due to the lack of automated and accurate segmentation ...

Defining endotypes of bronchopulmonary dysplasia in preterm infants to improve precision-based therapies.

JCI insight
Bronchopulmonary dysplasia (BPD) remains a debilitating disease in premature infants. The chronic pathogenesis of BPD with complex prenatal and postnatal programming challenges attempts at precisely defining or treating disease. While existing BPD de...