AIMC Topic: Lung

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Improving diagnosis accuracy with an intelligent image retrieval system for lung pathologies detection: a features extractor approach.

Scientific reports Oct 3, 2023
Detecting lung pathologies is critical for precise medical diagnosis. In the realm of diagnostic methods, various approaches, including imaging tests, physical examinations, and laboratory tests, contribute to this process. Of particular note, imagin...
Artificial Intelligence Algorithms Radiography Tomography, X-Ray Computed Lung
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External validation, radiological evaluation, and development of deep learning automatic lung segmentation in contrast-enhanced chest CT.

European radiology Sep 29, 2023
OBJECTIVES: There is a need for CT pulmonary angiography (CTPA) lung segmentation models. Clinical translation requires radiological evaluation of model outputs, understanding of limitations, and identification of failure points. This multicentre stu...
Tomography, X-Ray Computed Hypertension, Pulmonary Artificial Intelligence Lung Humans Deep Learning Retrospective Studies Lung Diseases, Interstitial
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DeepHistoNet: A robust deep-learning model for the classification of hepatocellular, lung, and colon carcinoma.

Microscopy research and technique Sep 26, 2023
In recent days, non-communicable diseases (NCDs) require more attention since they require specialized infrastructure for treatment. As per the cancer population registry estimate, nearly 800,000 new cancer cases will be detected yearly. The statisti...
Humans Machine Learning Carcinoma, Hepatocellular Deep Learning Liver Neoplasms Colon Lung
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Extracting lung contour deformation features with deep learning for internal target motion tracking: a preliminary study.

Physics in medicine and biology Sep 22, 2023
. To propose lung contour deformation features (LCDFs) as a surrogate to estimate the thoracic internal target motion, and to report their performance by correlating with the changing body using a cascade ensemble model (CEM). LCDFs, correlated to th...
Humans Algorithms Lung Neoplasms Motion Lung Respiration Deep Learning
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Deep Learning Neural Network-Guided Detection of Asbestos Bodies in Bronchoalveolar Lavage Samples.

Acta cytologica Sep 19, 2023
INTRODUCTION: Asbestos is a global occupational health hazard, and exposure to it by inhalation predisposes to interstitial as well as malignant pulmonary morbidity. Over time, asbestos fibers embedded in lung tissue can become coated with iron-rich ...
Bronchoalveolar Lavage Fluid Asbestos Humans Bronchoalveolar Lavage Lung Deep Learning Occupational Exposure
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Effects of driving pressure-guided ventilation by individualized positive end-expiratory pressure on oxygenation undergoing robot-assisted laparoscopic radical prostatectomy: a randomized controlled clinical trial.

Journal of anesthesia Sep 14, 2023
PURPOSE: Patients with robot-assisted laparoscopic radical prostatectomy (RALP) need to be placed in Trendelenburg position, which results in cranial displacement of the diaphragm and decreases functional residual capacity and pulmonary compliance. P...
Humans Lung Positive-Pressure Respiration Male Prostatectomy Robotics Laparoscopy
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Predicting successful clinical candidates for fiducial-free lung tumor tracking with a deep learning binary classification model.

Journal of applied clinical medical physics Sep 11, 2023
OBJECTIVES: The CyberKnife system is a robotic radiosurgery platform that allows the delivery of lung SBRT treatments using fiducial-free soft-tissue tracking. However, not all lung cancer patients are eligible for lung tumor tracking. Tumor size, de...
Humans Computer Simulation Lung Neoplasms Robotics Lung Deep Learning
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Simultaneous object detection and segmentation for patient-specific markerless lung tumor tracking in simulated radiographs with deep learning.

Medical physics Sep 8, 2023
BACKGROUND: Real-time tumor tracking is one motion management method to address motion-induced uncertainty. To date, fiducial markers are often required to reliably track lung tumors with X-ray imaging, which carries risks of complications and leads ...
Lung Neoplasms Fiducial Markers Humans Algorithms Deep Learning Lung Image Processing, Computer-Assisted
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Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound.

IEEE journal of biomedical and health informatics Sep 6, 2023
Lung ultrasound (LUS) is an important imaging modality used by emergency physicians to assess pulmonary congestion at the patient bedside. B-line artifacts in LUS videos are key findings associated with pulmonary congestion. Not only can the interpre...
Pulmonary Edema Thorax Humans Lung Deep Learning Ultrasonography
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A novel image deep learning-based sub-centimeter pulmonary nodule management algorithm to expedite resection of the malignant and avoid over-diagnosis of the benign.

European radiology Sep 2, 2023
OBJECTIVES: With the popularization of chest computed tomography (CT) screening, there are more sub-centimeter (≤ 1 cm) pulmonary nodules (SCPNs) requiring further diagnostic workup. This area represents an important opportunity to optimize the SCPN ...
Precancerous Conditions Overdiagnosis Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Algorithms Lung Humans Lung Neoplasms Deep Learning Multiple Pulmonary Nodules
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