AIMC Topic: Tomography, X-Ray Computed
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Deep learning reconstruction for zero echo time lung magnetic resonance imaging: impact on image quality and lesion detection.
Clinical radiology
Jul 17, 2024
AIMS: This study aimed to examine the impact of deep-learning reconstruction (DLR) on zero echo time (ZTE) lung MRI.
3D U-Net Neural Network Architecture-Assisted LDCT to Acquire Vertebral Morphology Parameters: A Vertebral Morphology Comprehensive Analysis in a Chinese Population.
Calcified tissue international
Jul 17, 2024
To evaluate the feasibility of acquiring vertebral height from chest low-dose computed tomography (LDCT) images using an artificial intelligence (AI) system based on 3D U-Net vertebral segmentation technology and the correlation and features of verte...
Finite element models with automatic computed tomography bone segmentation for failure load computation.
Scientific reports
Jul 17, 2024
Bone segmentation is an important step to perform biomechanical failure load simulations on in-vivo CT data of patients with bone metastasis, as it is a mandatory operation to obtain meshes needed for numerical simulations. Segmentation can be a tedi...
Streak artefact removal in x-ray dark-field computed tomography using a convolutional neural network.
Medical physics
Jul 16, 2024
BACKGROUND: Computed tomography (CT) relies on the attenuation of x-rays, and is, hence, of limited use for weakly attenuating organs of the body, such as the lung. X-ray dark-field (DF) imaging is a recently developed technology that utilizes x-ray ...
Prediction of hematoma expansion in spontaneous intracerebral hemorrhage using a multimodal neural network.
Scientific reports
Jul 16, 2024
Hematoma expansion occasionally occurs in patients with intracerebral hemorrhage (ICH), associating with poor outcome. Multimodal neural networks incorporating convolutional neural network (CNN) analysis of images and neural network analysis of tabul...
Integrating Artificial Intelligence Into the Visualization and Modeling of Three-Dimensional Anatomy in Pediatric Surgical Patients.
Journal of pediatric surgery
Jul 15, 2024
BACKGROUND: Pediatric surgeons often treat patients with complex anatomical considerations due to congenital anomalies or distortion of normal structures by solid organ tumors. There are multiple applications for three-dimensional visualization of th...
Self-adaptive deep learning-based segmentation for universal and functional clinical and preclinical CT image analysis.
Computers in biology and medicine
Jul 15, 2024
BACKGROUND: Methods to monitor cardiac functioning non-invasively can accelerate preclinical and clinical research into novel treatment options for heart failure. However, manual image analysis of cardiac substructures is resource-intensive and error...
Developing an explainable diagnosis system utilizing deep learning model: a case study of spontaneous pneumothorax.
Physics in medicine and biology
Jul 15, 2024
The trend in the medical field is towards intelligent detection-based medical diagnostic systems. However, these methods are often seen as 'black boxes' due to their lack of interpretability. This situation presents challenges in identifying reasons ...
Preoperative Contrast-Enhanced CT-Based Deep Learning Radiomics Model for Distinguishing Retroperitoneal Lipomas and Well‑Differentiated Liposarcomas.
Academic radiology
Jul 14, 2024
RATIONALE AND OBJECTIVES: To assess the efficacy of a preoperative contrast-enhanced CT (CECT)-based deep learning radiomics nomogram (DLRN) for predicting murine double minute 2 (MDM2) gene amplification as a means of distinguishing between retroper...
Combined deep learning and radiomics in pretreatment radiation esophagitis prediction for patients with esophageal cancer underwent volumetric modulated arc therapy.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jul 14, 2024
PURPOSE: To develop a combined radiomics and deep learning (DL) model in predicting radiation esophagitis (RE) of a grade ≥ 2 for patients with esophageal cancer (EC) underwent volumetric modulated arc therapy (VMAT) based on computed tomography (CT)...
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