AI Medical Compendium Topic:
Tomography, X-Ray Computed

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A novel model for predicting postoperative liver metastasis in R0 resected pancreatic neuroendocrine tumors: integrating computational pathology and deep learning-radiomics.

Journal of translational medicine Aug 14, 2024
BACKGROUND: Postoperative liver metastasis significantly impacts the prognosis of pancreatic neuroendocrine tumor (panNET) patients after R0 resection. Combining computational pathology and deep learning radiomics can enhance the detection of postope...
Middle Aged Deep Learning Liver Neoplasms Nomograms Pancreatic Neoplasms Postoperative Period Multivariate Analysis Neuroendocrine Tumors Aged Adult Radiomics Male Prognosis Tomography, X-Ray Computed Female Humans
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Hierarchical multi-level dynamic hyperparameter deformable image registration with convolutional neural network.

Physics in medicine and biology Aug 14, 2024
. To enable the registration network to be trained only once, achieving fast regularization hyperparameter selection during the inference phase, and to improve registration accuracy and deformation field regularity.. Hyperparameter tuning is an essen...
Humans Neural Networks, Computer Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted
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Automatic segmentation of high-risk clinical target volume and organs at risk in brachytherapy of cervical cancer with a convolutional neural network.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique Aug 14, 2024
PURPOSE: This study aimed to design an autodelineation model based on convolutional neural networks for generating high-risk clinical target volumes and organs at risk in image-guided adaptive brachytherapy for cervical cancer.
Rectum Colon, Sigmoid Organs at Risk Radiotherapy Planning, Computer-Assisted Female Brachytherapy Humans Adult Neural Networks, Computer Urinary Bladder Uterine Cervical Neoplasms Tomography, X-Ray Computed Radiotherapy, Image-Guided Middle Aged
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The Usefulness of Low-Kiloelectron Volt Virtual Monochromatic Contrast-Enhanced Computed Tomography with Deep Learning Image Reconstruction Technique in Improving the Delineation of Pancreatic Ductal Adenocarcinoma.

Journal of imaging informatics in medicine Aug 13, 2024
To evaluate the usefulness of low-keV multiphasic computed tomography (CT) with deep learning image reconstruction (DLIR) in improving the delineation of pancreatic ductal adenocarcinoma (PDAC) compared to conventional hybrid iterative reconstruction...
Middle Aged Deep Learning Image Processing, Computer-Assisted Contrast Media Pancreatic Neoplasms Radiographic Image Interpretation, Computer-Assisted Carcinoma, Pancreatic Ductal Aged Humans Aged, 80 and over Retrospective Studies Adult Tomography, X-Ray Computed Male Female
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A machine learning-based pipeline for multi-organ/tissue patient-specific radiation dosimetry in CT.

European radiology Aug 13, 2024
OBJECTIVES: To develop a machine learning-based pipeline for multi-organ/tissue personalized radiation dosimetry in CT.
Male Middle Aged Radiation Dosage Monte Carlo Method Radiometry Tomography, X-Ray Computed Humans Female Neural Networks, Computer Aged Machine Learning Adult Retrospective Studies
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Three-Dimensional Deep Learning Normal Tissue Complication Probability Model to Predict Late Xerostomia in Patients With Head and Neck Cancer.

International journal of radiation oncology, biology, physics Aug 13, 2024
PURPOSE: Conventional normal tissue complication probability (NTCP) models for patients with head and neck cancer are typically based on single-value variables, which, for radiation-induced xerostomia, are baseline xerostomia and mean salivary gland ...
Adult Male Middle Aged Deep Learning Tomography, X-Ray Computed Radiation Injuries Female Head and Neck Neoplasms Salivary Glands Aged Organs at Risk Humans Xerostomia Aged, 80 and over Probability Radiotherapy Dosage
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Deep learning models for separate segmentations of intracerebral and intraventricular hemorrhage on head CT and segmentation quality assessment.

Medical physics Aug 12, 2024
BACKGROUND: The volume measurement of intracerebral hemorrhage (ICH) and intraventricular hemorrhage (IVH) provides critical information for precise treatment of patients with spontaneous ICH but remains a big challenge, especially for IVH segmentati...
Image Processing, Computer-Assisted Cerebral Hemorrhage Quality Control Head Humans Tomography, X-Ray Computed Deep Learning
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Dual-branch Transformer for semi-supervised medical image segmentation.

Journal of applied clinical medical physics Aug 12, 2024
PURPOSE: In recent years, the use of deep learning for medical image segmentation has become a popular trend, but its development also faces some challenges. Firstly, due to the specialized nature of medical data, precise annotation is time-consuming...
Humans Neural Networks, Computer COVID-19 Algorithms Supervised Machine Learning Tomography, X-Ray Computed SARS-CoV-2 Deep Learning Image Processing, Computer-Assisted
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Unraveling phenotypic heterogeneity in stanford type B aortic dissection patients through machine learning clustering analysis of cardiovascular CT imaging.

Hellenic journal of cardiology : HJC = Hellenike kardiologike epitheorese Aug 10, 2024
OBJECTIVE: Aortic dissection remains a life-threatening condition necessitating accurate diagnosis and timely intervention. This study aimed to investigate phenotypic heterogeneity in patients with Stanford type B aortic dissection (TBAD) through mac...
Humans Machine Learning Phenotype Cluster Analysis Aortic Dissection Aortic Aneurysm, Thoracic Computed Tomography Angiography Adult Male Retrospective Studies Middle Aged Tomography, X-Ray Computed Imaging, Three-Dimensional Female Aged
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Accuracy and time efficiency of a novel deep learning algorithm for Intracranial Hemorrhage detection in CT Scans.

La Radiologia medica Aug 9, 2024
PURPOSE: To evaluate a deep learning-based pipeline using a Dense-UNet architecture for the assessment of acute intracranial hemorrhage (ICH) on non-contrast computed tomography (NCCT) head scans after traumatic brain injury (TBI).
Humans Sensitivity and Specificity Algorithms Male Retrospective Studies Middle Aged Tomography, X-Ray Computed Deep Learning Female Aged Time Factors Aged, 80 and over Brain Injuries, Traumatic Adult Intracranial Hemorrhages
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