AIMC Topic: Tomography, X-Ray Computed
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A position-enhanced sequential feature encoding model for lung infections and lymphoma classification on CT images.
International journal of computer assisted radiology and surgery
Jul 14, 2024
PURPOSE: Differentiating pulmonary lymphoma from lung infections using CT images is challenging. Existing deep neural network-based lung CT classification models rely on 2D slices, lacking comprehensive information and requiring manual selection. 3D ...
Model based on the automated AI-driven CT quantification is effective for the diagnosis of refractory Mycoplasma pneumoniae pneumonia.
Scientific reports
Jul 13, 2024
The prediction of refractory Mycoplasma pneumoniae pneumonia (RMPP) remains a clinically significant challenge. This study aimed to develop an early predictive model utilizing artificial intelligence (AI)-derived quantitative assessment of lung lesio...
Comparative assessment of the capability of machine learning-based radiomic models for predicting omental metastasis in locally advanced gastric cancer.
Scientific reports
Jul 13, 2024
The study aims to investigate the predictive capability of machine learning algorithms for omental metastasis in locally advanced gastric cancer (LAGC) and to compare the performance metrics of various machine learning predictive models. A retrospect...
Automatic 3D reconstruction of vertebrae from orthogonal bi-planar radiographs.
Scientific reports
Jul 13, 2024
When conducting spine-related diagnosis and surgery, the three-dimensional (3D) upright posture of the spine under natural weight bearing is of significant clinical value for physicians to analyze the force on the spine. However, existing medical ima...
A Novel Deep Learning-based Artificial Intelligence System for Interpreting Urolithiasis in Computed Tomography.
European urology focus
Jul 12, 2024
BACKGROUND AND OBJECTIVE: Our aim was to develop an artificial intelligence (AI) system for detection of urolithiasis in computed tomography (CT) images using advanced deep learning capable of real-time calculation of stone parameters such as volume ...
Fair AI-powered orthopedic image segmentation: addressing bias and promoting equitable healthcare.
Scientific reports
Jul 12, 2024
AI-powered segmentation of hip and knee bony anatomy has revolutionized orthopedics, transforming pre-operative planning and post-operative assessment. Despite the remarkable advancements in AI algorithms for medical imaging, the potential for biases...
A Computed Tomography-Based Fracture Prediction Model With Images of Vertebral Bones and Muscles by Employing Deep Learning: Development and Validation Study.
Journal of medical Internet research
Jul 12, 2024
BACKGROUND: With the progressive increase in aging populations, the use of opportunistic computed tomography (CT) scanning is increasing, which could be a valuable method for acquiring information on both muscles and bones of aging populations.
Enhanced deep learning model for precise nodule localization and recurrence risk prediction following curative-intent surgery for lung cancer.
PloS one
Jul 12, 2024
PURPOSE: Radical surgery is the primary treatment for early-stage resectable lung cancer, yet recurrence after curative surgery is not uncommon. Identifying patients at high risk of recurrence using preoperative computed tomography (CT) images could ...
Predicting Secondary Vertebral Compression Fracture After Vertebral Augmentation via CT-Based Machine Learning Radiomics-Clinical Model.
Academic radiology
Jul 10, 2024
RATIONALE AND OBJECTIVES: Secondary vertebral compression fractures (SVCF) are very common in patients after vertebral augmentation (VA). The aim of this study was to establish a radiomic-based model to predict SVCF and specify appropriate treatment ...
Deep learning in pulmonary nodule detection and segmentation: a systematic review.
European radiology
Jul 10, 2024
OBJECTIVES: The accurate detection and precise segmentation of lung nodules on computed tomography are key prerequisites for early diagnosis and appropriate treatment of lung cancer. This study was designed to compare detection and segmentation metho...
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