AIMC Topic: Tomography, X-Ray Computed
Clear Filters Showing 171 to 180 of 4956 articles
A deep learning model combining circulating tumor cells and radiological features in the multi-classification of mediastinal lesions in comparison with thoracic surgeons: a large-scale retrospective study.
BMC medicine
May 7, 2025
BACKGROUND: CT images and circulating tumor cells (CTCs) are indispensable for diagnosing the mediastinal lesions by providing radiological and intra-tumoral information. This study aimed to develop and validate a deep multimodal fusion network (DMFN...
Enhancing efficient deep learning models with multimodal, multi-teacher insights for medical image segmentation.
Scientific reports
May 7, 2025
The rapid evolution of deep learning has dramatically enhanced the field of medical image segmentation, leading to the development of models with unprecedented accuracy in analyzing complex medical images. Deep learning-based segmentation holds signi...
Optimizing Strategy for Lung Cancer Screening: From Risk Prediction to Clinical Decision Support.
JCO clinical cancer informatics
May 7, 2025
PURPOSE: Low-dose computed tomography (LDCT) screening is effective in reducing lung cancer mortality by detecting the disease at earlier, more treatable stages. However, high false-positive rates and the associated risks of subsequent invasive diagn...
BentRay-NeRF: Bent-Ray Neural Radiance Fields for Robust Speed-of-Sound Imaging in Ultrasound Computed Tomography.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
May 7, 2025
Ultrasound computed tomography (USCT) is a promising technique for breast cancer detection because of its quantitative imaging capability of the speed of sound (SOS) of soft tissues and the fact that malignant breast lesions often have a higher SOS c...
Stacking classifiers based on integrated machine learning model: fusion of CT radiomics and clinical biomarkers to predict lymph node metastasis in locally advanced gastric cancer patients after neoadjuvant chemotherapy.
BMC cancer
May 6, 2025
BACKGROUND: The early prediction of lymph node positivity (LN+) after neoadjuvant chemotherapy (NAC) is crucial for optimizing individualized treatment strategies. This study aimed to integrate radiomic features and clinical biomarkers through machin...
The Role of Computed Tomography and Artificial Intelligence in Evaluating the Comorbidities of Chronic Obstructive Pulmonary Disease: A One-Stop CT Scanning for Lung Cancer Screening.
International journal of chronic obstructive pulmonary disease
May 6, 2025
Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide. Comorbidities in patients with COPD significantly increase morbidity, mortality, and healthcare costs, posing a significant burden on the management o...
Interpretable Prognostic Modeling for Postoperative Pancreatic Cancer Using Multi-machine Learning and Habitat Radiomics: A Multi-center Study.
Academic radiology
May 5, 2025
RATIONALE AND OBJECTIVES: Accurate risk stratification is critical for guiding personalized treatment in resectable pancreatic cancer (RPC). This retrospective study assessed the utility of habitat radiomics for predicting recurrence-free survival (R...
Detecting wing fractures in chickens using deep learning, photographs and computed tomography scanning.
Poultry science
May 5, 2025
Animal welfare monitoring is a key part of veterinary surveillance in every poultry slaughterhouse. Among the animal welfare indicators routinely inspected, the prevalence of wing fractures and soft tissues injuries (e.g. bruises) is particularly rel...
Prediction of EGFR Mutations in Lung Adenocarcinoma via CT Images: A Comparative Study of Intratumoral and Peritumoral Radiomics, Deep Learning, and Fusion Models.
Academic radiology
May 5, 2025
RATIONALE AND OBJECTIVES: This study aims to analyze the intratumoral and peritumoral characteristics of lung adenocarcinoma patients on the basis of chest CT images via radiomic and deep learning methods and to develop and validate a multimodel fusi...
Integrating anatomy and electrophysiology in the healthy human heart: Insights from biventricular statistical shape analysis using universal coordinates.
Computers in biology and medicine
May 4, 2025
A cardiac digital twin is a virtual replica of a patient-specific heart, mimicking its anatomy and physiology. A crucial step of building a cardiac digital twin is anatomical twinning, where the computational mesh of the digital twin is tailored to t...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32510
- Neural Networks, Computer 30481
- Algorithms 27731
- Deep Learning 27277
- Artificial Intelligence 25203
- Robotics 13428
- Image Processing, Computer-Assisted 9883
- Retrospective Studies 9527
- Magnetic Resonance Imaging 6481
- Reproducibility of Results 5744
- Tomography, X-Ray Computed 4956
- Support Vector Machine 4812
- Computational Biology 4392
- Brain 4186
- Computer Simulation 3962
Recent Journals
- Scientific reports 7009
- Sensors (Basel, Switzerland) 4794
- PloS one 4295
- Neural networks : the official journal of the International Neural Network Society 3035
- Computers in biology and medicine 2037
- Computational intelligence and neuroscience 1931
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1395
- IEEE journal of biomedical and health informatics 1191
- Journal of chemical information and modeling 1083
- Nature communications 1070
- Computer methods and programs in biomedicine 895
- Bioinformatics (Oxford, England) 879
- Journal of medical Internet research 878
- IEEE transactions on neural networks and learning systems 859