AIMC Topic: Lung Neoplasms

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Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule Characterization.

Tomography (Ann Arbor, Mich.)
BACKGROUND/OBJECTIVES: Correct pulmonary nodule volumetry and categorization is paramount for accurate diagnosis in lung cancer screening programs. CT scanners with slice thicknesses of multiple millimetres are still common worldwide, and slice thick...

Enhancing Diagnostic Accuracy of Lung Nodules in Chest Computed Tomography Using Artificial Intelligence: Retrospective Analysis.

Journal of medical Internet research
BACKGROUND: Uncertainty in the diagnosis of lung nodules is a challenge for both patients and physicians. Artificial intelligence (AI) systems are increasingly being integrated into medical imaging to assist diagnostic procedures. However, the accura...

Feature-targeted deep learning framework for pulmonary tumorous Cone-beam CT (CBCT) enhancement with multi-task customized perceptual loss and feature-guided CycleGAN.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Thoracic Cone-beam computed tomography (CBCT) is routinely collected during image-guided radiation therapy (IGRT) to provide updated patient anatomy information for lung cancer treatments. However, CBCT images often suffer from streaking artifacts an...

Brachytherapy Seed Placement by Robotic Bronchoscopy with Cone Beam Computed Tomography Guidance for Peripheral Lung Cancer: A Human Cadaveric Feasibility Pilot.

International journal of radiation oncology, biology, physics
PURPOSE: This study evaluates the feasibility of using robotic-assisted bronchoscopy with cone beam computed tomography (RB-CBCT) platform to perform low-dose-rate brachytherapy (LDR-BT) implants in a mechanically ventilated human cadaveric model. Po...

NAVT-net neuron attention visual taylor network for lung cancer detection using CT images.

Computational biology and chemistry
Lung Cancer is regarded as a common fatal disease affecting humans throughout the entire world. Early diagnosis is vital to save the patient's life and Computed Tomography (CT) scans are referred to as the major imaging modes but, the manual examinat...

Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma.

Scientific reports
To integrate machine learning and multiomic data on lactylation-related genes (LRGs) for molecular typing and prognosis prediction in lung adenocarcinoma (LUAD). LRG mRNA and long non-coding RNA transcriptomes, epigenetic methylation data, and somati...

Delta-Radiomics Using Machine Learning Classifiers With Auxiliary Data Sets to Predict Disease Progression During Magnetic Resonance-Guided Radiotherapy in Adrenal Metastases.

JCO clinical cancer informatics
PURPOSE: Adaptive radiotherapy accounts for interfractional anatomic changes. We hypothesize that changes in the gross tumor volumes identified during daily scans could be analyzed using delta-radiomics to predict disease progression events. We evalu...

Large Language Model Approach for Zero-Shot Information Extraction and Clustering of Japanese Radiology Reports: Algorithm Development and Validation.

JMIR cancer
BACKGROUND: The application of natural language processing in medicine has increased significantly, including tasks such as information extraction and classification. Natural language processing plays a crucial role in structuring free-form radiology...

Colorimetric aptasensor coupled with a deep-learning-powered smartphone app for programmed death ligand-1 expressing extracellular vesicles.

Frontiers in immunology
Lung cancer is a devastating public health threat and a leading cause of cancer-related deaths. Therefore, it is imperative to develop sophisticated techniques for the non-invasive detection of lung cancer. Extracellular vesicles expressing programme...

Deep learning-based synthetic CT for dosimetric monitoring of combined conventional radiotherapy and lattice boost in large lung tumors.

Radiation oncology (London, England)
PURPOSE: Conventional radiotherapy (CRT) has limited local control and poses a high risk of severe toxicity in large lung tumors. This study aimed to develop an integrated treatment plan that combines CRT with lattice boost radiotherapy (LRT) and mon...