AIMC Topic: Lung Neoplasms

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Dual segmentation models for poorly and well-differentiated hepatocellular carcinoma using two-step transfer deep learning on dynamic contrast-enhanced CT images.

Physical and engineering sciences in medicine Dec 5, 2022
The aim of this study was to develop dual segmentation models for poorly and well-differentiated hepatocellular carcinoma (HCC), using two-step transfer learning (TSTL) based on dynamic contrast-enhanced (DCE) computed tomography (CT) images. From 20...
Tomography, X-Ray Computed Deep Learning Carcinoma, Hepatocellular Lung Neoplasms Liver Neoplasms Humans
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Deep learning-based motion compensation for four-dimensional cone-beam computed tomography (4D-CBCT) reconstruction.

Medical physics Dec 3, 2022
BACKGROUND: Motion-compensated (MoCo) reconstruction shows great promise in improving four-dimensional cone-beam computed tomography (4D-CBCT) image quality. MoCo reconstruction for a 4D-CBCT could be more accurate using motion information at the CBC...
Deep Learning Cone-Beam Computed Tomography Image Processing, Computer-Assisted Humans Algorithms Phantoms, Imaging Four-Dimensional Computed Tomography Lung Neoplasms Spiral Cone-Beam Computed Tomography Motion
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Validation of a Deep Learning-Based Model to Predict Lung Cancer Risk Using Chest Radiographs and Electronic Medical Record Data.

JAMA network open Dec 1, 2022
IMPORTANCE: Lung cancer screening with chest computed tomography (CT) prevents lung cancer death; however, fewer than 5% of eligible Americans are screened. CXR-LC, an open-source deep learning tool that estimates lung cancer risk from existing chest...
Lung Neoplasms United States Middle Aged Deep Learning Early Detection of Cancer Medicare Humans Electronic Health Records Aged Male Female
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Using Tree-Based Machine Learning for Health Studies: Literature Review and Case Series.

International journal of environmental research and public health Dec 1, 2022
Tree-based machine learning methods have gained traction in the statistical and data science fields. They have been shown to provide better solutions to various research questions than traditional analysis approaches. To encourage the uptake of tree-...
Humans Machine Learning Female Propensity Score Lung Neoplasms Bayes Theorem
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Effect of da Vinci robot-assisted versus traditional thoracoscopic bronchial sleeve lobectomy.

Asian journal of surgery Nov 28, 2022
OBJECTIVE: To analyze the short-term effect of Da Vinci robot-assisted thoracoscopic (RATS) bronchial sleeve lobectomy, so as to summarize its safety and effectiveness.
Lymph Node Excision Robotics Thoracic Surgery, Video-Assisted Pneumonectomy Lung Neoplasms Humans Carcinoma, Non-Small-Cell Lung Retrospective Studies
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Deep learning-based internal gross target volume definition in 4D CT images of lung cancer patients.

Medical physics Nov 25, 2022
BACKGROUND: Contouring of internal gross target volume (iGTV) is an essential part of treatment planning in radiotherapy to mitigate the impact of intra-fractional target motion. However, it is usually time-consuming and easily subjected to intra-obs...
Tumor Burden Four-Dimensional Computed Tomography Image Processing, Computer-Assisted Humans Lung Neoplasms Deep Learning Radiotherapy Planning, Computer-Assisted
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Explainability and controllability of patient-specific deep learning with attention-based augmentation for markerless image-guided radiotherapy.

Medical physics Nov 24, 2022
BACKGROUND: We reported the concept of patient-specific deep learning (DL) for real-time markerless tumor segmentation in image-guided radiotherapy (IGRT). The method was aimed to control the attention of convolutional neural networks (CNNs) by artif...
Lung Neoplasms Radiotherapy, Image-Guided Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Retrospective Studies Humans
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Development and performance evaluation of a deep learning lung nodule detection system.

BMC medical imaging Nov 22, 2022
BACKGROUND: Lung cancer is the leading cause of cancer-related deaths throughout the world. Chest computed tomography (CT) is now widely used in the screening and diagnosis of lung cancer due to its effectiveness. Radiologists must identify each smal...
Deep Learning Humans Lung Neoplasms Tomography, X-Ray Computed Phantoms, Imaging Lung
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Deep learning-based dynamic PET parametric K image generation from lung static PET.

European radiology Nov 18, 2022
OBJECTIVES: PET/CT is a first-line tool for the diagnosis of lung cancer. The accuracy of quantification may suffer from various factors throughout the acquisition process. The dynamic PET parametric K provides better quantification and improve speci...
Deep Learning Image Processing, Computer-Assisted Positron Emission Tomography Computed Tomography Positron-Emission Tomography Lung Neoplasms Humans Lung
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Deep multiple instance learning for predicting chemotherapy response in non-small cell lung cancer using pretreatment CT images.

Scientific reports Nov 18, 2022
The individual prognosis of chemotherapy is quite different in non-small cell lung cancer (NSCLC). There is an urgent need to precisely predict and assess the treatment response. To develop a deep multiple-instance learning (DMIL) based model for pre...
Carcinoma, Non-Small-Cell Lung Area Under Curve Tomography, X-Ray Computed Humans Deep Learning Lung Neoplasms
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