AIMC Topic: Tomography, X-Ray Computed
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Descriptive overview of AI applications in x-ray imaging and radiotherapy.
Journal of radiological protection : official journal of the Society for Radiological Protection
Dec 27, 2024
Artificial intelligence (AI) is transforming medical radiation applications by handling complex data, learning patterns, and making accurate predictions, leading to improved patient outcomes. This article examines the use of AI in optimising radiatio...
Deep Learning Model for the Differential Diagnosis of Nasal Polyps and Inverted Papilloma by CT Images: A Multicenter Study.
Academic radiology
Dec 26, 2024
RATIONALE AND OBJECTIVES: Nasal polyps (NP) and inverted papilloma (IP) are benign tumors within the nasal cavity, each necessitating distinct treatment approaches. Herein, we investigate the utility of a deep learning (DL) model for distinguishing b...
Machine learning-based pipeline for automated intracerebral hemorrhage and drain detection, quantification, and classification in non-enhanced CT images (NeuroDrAIn).
PloS one
Dec 26, 2024
BACKGROUND AND PURPOSE: External drainage represents a well-established treatment option for acute intracerebral hemorrhage. The current standard of practice includes post-operative computer tomography imaging, which is subjectively evaluated. The im...
Correlation between individual thigh muscle volume and grip strength in relation to sarcopenia with automated muscle segmentation.
PloS one
Dec 26, 2024
INTRODUCTION: Grip strength serves as a significant marker for diagnosing and assessing sarcopenia, particularly in elderly populations. The study aims to explore the relationship between individual thigh muscle volumes and grip strength, leveraging ...
Accuracy of machine learning models for pre-diagnosis and diagnosis of pancreatic ductal adenocarcinoma in contrast-CT images: a systematic review and meta-analysis.
Abdominal radiology (New York)
Dec 25, 2024
PURPOSE: To evaluate the diagnostic ability and methodological quality of ML models in detecting Pancreatic Ductal Adenocarcinoma (PDAC) in Contrast CT images.
Prior-FOVNet: A Multimodal Deep Learning Framework for Megavoltage Computed Tomography Truncation Artifact Correction and Field-of-View Extension.
Sensors (Basel, Switzerland)
Dec 25, 2024
Megavoltage computed tomography (MVCT) plays a crucial role in patient positioning and dose reconstruction during tomotherapy. However, due to the limited scan field of view (sFOV), the entire cross-section of certain patients may not be fully covere...
Predicting lymph node metastasis in thyroid cancer: systematic review and meta-analysis on the CT/MRI-based radiomics and deep learning models.
Clinical imaging
Dec 24, 2024
BACKGROUND: Thyroid cancer, a common endocrine malignancy, has seen increasing incidence, making lymph node metastasis (LNM) a critical factor for recurrence and survival. Radiomics and deep learning (DL) advancements offer the potential for improved...
Mask R-CNN assisted diagnosis of spinal tuberculosis.
Journal of X-ray science and technology
Dec 24, 2024
The prevalence of spinal tuberculosis (ST) is particularly high in underdeveloped regions with inadequate medical conditions. This not only leads to misdiagnosis and delays in treatment progress but also contributes to the continued transmission of t...
Prognostic value of a composite physiologic index developed by adding bronchial and hyperlucent volumes quantified via artificial intelligence technology.
Respiratory research
Dec 24, 2024
BACKGROUND: The composite physiologic index (CPI) was developed to estimate the extent of interstitial lung disease (ILD) in idiopathic pulmonary fibrosis (IPF) patients based on pulmonary function tests (PFTs). The CALIPER-revised version of the CPI...
Fusion-driven semi-supervised learning-based lung nodules classification with dual-discriminator and dual-generator generative adversarial network.
BMC medical informatics and decision making
Dec 24, 2024
BACKGROUND: The detection and classification of lung nodules are crucial in medical imaging, as they significantly impact patient outcomes related to lung cancer diagnosis and treatment. However, existing models often suffer from mode collapse and po...
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