AIMC Topic: Tomography, X-Ray Computed
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Preoperative assessment in lymph node metastasis of pancreatic ductal adenocarcinoma: a transformer model based on dual-energy CT.
World journal of surgical oncology
Apr 9, 2025
BACKGROUND: Deep learning(DL) models can improve significantly discrimination of lymph node metastasis(LNM) of pancreatic ductal adenocarcinoma(PDAC), but have not been systematically assessed.
Machine learning prediction of effective radiation doses in various computed tomography applications: a virtual human phantom study.
Biomedizinische Technik. Biomedical engineering
Apr 8, 2025
OBJECTIVES: In this work, it was aimed to employ machine learning (ML) algorithms to accurately forecast the radiation doses for phantoms while accounting for the most popular CT protocols.
NeuroNasal: Advanced AI-Driven Self-Supervised Learning Approach for Enhanced Sinonasal Pathology Detection.
Sensors (Basel, Switzerland)
Apr 8, 2025
Sinus diseases are inflammations or infections of the sinuses that significantly impact patient quality of life. They cause nasal congestion, facial pain, headaches, thick nasal discharge, and a reduced sense of smell. However, accurately diagnosing ...
Rapid dose prediction for lung CyberKnife radiotherapy plans utilizing a deep learning approach by incorporating dosimetric features delivered by noncoplanar beams.
Biomedical physics & engineering express
Apr 8, 2025
. The dose distribution of lung cancer patients treated with the CyberKnife (CK) system is influenced by various factors, including tumor location and the direction of CK beams. The objective of this study is to present a deep learning approach that ...
Skull CT metadata for automatic bone age assessment by using three-dimensional deep learning framework.
International journal of legal medicine
Apr 7, 2025
Bone age assessment (BAA) means challenging tasks in forensic science especially in some extreme situations like only skulls found. This study aimed to develop an accurate three-dimensional deep learning (DL) framework at skull CT metadata for BAA an...
Phantom-based evaluation of image quality in Transformer-enhanced 2048-matrix CT imaging at low and ultralow doses.
Japanese journal of radiology
Apr 7, 2025
PURPOSE: To compare the quality of standard 512-matrix, standard 1024-matrix, and Swin2SR-based 2048-matrix phantom images under different scanning protocols.
Validation of body composition parameters extracted via deep learning-based segmentation from routine computed tomographies.
Scientific reports
Apr 7, 2025
Sarcopenia and body composition metrics are strongly associated with patient outcomes. In this study, we developed and validated a flexible, open-access pipeline integrating available deep learning-based segmentation models with pre- and postprocessi...
Virtual lung screening trial (VLST): An in silico study inspired by the national lung screening trial for lung cancer detection.
Medical image analysis
Apr 5, 2025
Clinical imaging trials play a crucial role in advancing medical innovation but are often costly, inefficient, and ethically constrained. Virtual Imaging Trials (VITs) present a solution by simulating clinical trial components in a controlled, risk-f...
Open-source deep-learning models for segmentation of normal structures for prostatic and gynecological high-dose-rate brachytherapy: Comparison of architectures.
Journal of applied clinical medical physics
Apr 5, 2025
BACKGROUND: The use of deep learning-based auto-contouring algorithms in various treatment planning services is increasingly common. There is a notable deficit of commercially or publicly available models trained on large or diverse datasets containi...
MetaGP: A generative foundation model integrating electronic health records and multimodal imaging for addressing unmet clinical needs.
Cell reports. Medicine
Apr 4, 2025
Artificial intelligence makes strides in specialized diagnostics but faces challenges in complex clinical scenarios, such as rare disease diagnosis and emergency condition identification. To address these limitations, we develop Meta General Practiti...
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