AIMC Topic: Lung Neoplasms
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A patient-specific deep learning framework for 3D motion estimation and volumetric imaging during lung cancer radiotherapy.
Physics in medicine and biology
Jul 10, 2023
. Respiration introduces a constant source of irregular motion that poses a significant challenge for the precise irradiation of thoracic and abdominal cancers. Current real-time motion management strategies require dedicated systems that are not ava...
Deep learning-based age estimation from chest CT scans.
International journal of computer assisted radiology and surgery
Jul 7, 2023
PURPOSE: Medical imaging can be used to estimate a patient's biological age, which may provide complementary information to clinicians compared to chronological age. In this study, we aimed to develop a method to estimate a patient's age based on the...
Robot-assisted thoracoscopic right upper lobectomy with displaced B and absence of minor fissure: a case report.
Surgical and radiologic anatomy : SRA
Jul 7, 2023
INTRODUCTION: B downward-shifting is a rare bronchial anomaly characterized by abnormal pulmonary arteries associated with downward displacement of B and complete fusion between the right upper and middle lobes.
High accuracy epidermal growth factor receptor mutation prediction via histopathological deep learning.
BMC pulmonary medicine
Jul 5, 2023
BACKGROUND: The detection of epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer is critical for tyrosine kinase inhibitor therapy. EGFR detection requires tissue samples, which are difficult to obtain in som...
A systematic approach to deep learning-based nodule detection in chest radiographs.
Scientific reports
Jun 21, 2023
Lung cancer is a serious disease responsible for millions of deaths every year. Early stages of lung cancer can be manifested in pulmonary lung nodules. To assist radiologists in reducing the number of overseen nodules and to increase the detection a...
Deep-learning based fast and accurate 3D CT deformable image registration in lung cancer.
Medical physics
Jun 8, 2023
BACKGROUND: Deformable Image Registration (DIR) is an essential technique required in many applications of radiation oncology. However, conventional DIR approaches typically take several minutes to register one pair of 3D CT images and the resulting ...
Comparison and fusion prediction model for lung adenocarcinoma with micropapillary and solid pattern using clinicoradiographic, radiomics and deep learning features.
Scientific reports
Jun 8, 2023
To investigate whether the combination scheme of deep learning score (DL-score) and radiomics can improve preoperative diagnosis in the presence of micropapillary/solid (MPP/SOL) patterns in lung adenocarcinoma (ADC). A retrospective cohort of 514 co...
A deep-learning model using enhanced chest CT images to predict PD-L1 expression in non-small-cell lung cancer patients.
Clinical radiology
Jun 6, 2023
AIM: To develop a deep-learning model using contrast-enhanced chest computed tomography (CT) images to predict programmed death-ligand 1 (PD-L1) expression in patients with non-small-cell lung cancer (NSCLC).
Plasma Exosome Analysis for Protein Mutation Identification Using a Combination of Raman Spectroscopy and Deep Learning.
ACS sensors
Jun 6, 2023
Protein mutation detection using liquid biopsy can be simply performed periodically, making it easy to detect the occurrence of newly emerging mutations rapidly. However, it has low diagnostic accuracy since there are more normal proteins than mutate...
Robot-assisted segmentectomy with improved modified inflation-deflation combined with the intravenous indocyanine green method.
Journal of robotic surgery
Jun 5, 2023
To investigate the perioperative outcomes of patients who underwent robot-assisted thoracoscopic (RATS) segmentectomy for identifying the intersegmental plane (ISP) by improved modified inflation-deflation (MID) combined with near-infrared fluorescen...
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