AIMC Topic: Positron Emission Tomography Computed Tomography
Clear Filters Showing 61 to 70 of 322 articles
Deep learning-assisted interactive contouring of lung cancer: Impact on contouring time and consistency.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Sep 3, 2024
BACKGROUND AND PURPOSE: To evaluate the impact of a deep learning (DL)-assisted interactive contouring tool on inter-observer variability and the time taken to complete tumour contouring.
Evaluation of the prostate cancer and its metastases in the [ 68 Ga]Ga-PSMA PET/CT images: deep learning method vs. conventional PET/CT processing.
Nuclear medicine communications
Sep 3, 2024
PURPOSE: This study demonstrates the feasibility and benefits of using a deep learning-based approach for attenuation correction in [ 68 Ga]Ga-PSMA PET scans.
A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease.
Tomography (Ann Arbor, Mich.)
Sep 3, 2024
BACKGROUND: Cardiovascular disease affects the carotid arteries, coronary arteries, aorta and the peripheral arteries. Radiomics involves the extraction of quantitative data from imaging features that are imperceptible to the eye. Radiomics analysis ...
Deep learning with uncertainty estimation for automatic tumor segmentation in PET/CT of head and neck cancers: impact of model complexity, image processing and augmentation.
Biomedical physics & engineering express
Aug 30, 2024
Target volumes for radiotherapy are usually contoured manually, which can be time-consuming and prone to inter- and intra-observer variability. Automatic contouring by convolutional neural networks (CNN) can be fast and consistent but may produce unr...
Comparison of the Accuracy of a Deep Learning Method for Lesion Detection in PET/CT and PET/MRI Images.
Molecular imaging and biology
Aug 14, 2024
PURPOSE: Develop a universal lesion recognition algorithm for PET/CT and PET/MRI, validate it, and explore factors affecting performance.
Deep learning-aided respiratory motion compensation in PET/CT: addressing motion induced resolution loss, attenuation correction artifacts and PET-CT misalignment.
European journal of nuclear medicine and molecular imaging
Aug 13, 2024
PURPOSE: Respiratory motion (RM) significantly impacts image quality in thoracoabdominal PET/CT imaging. This study introduces a unified data-driven respiratory motion correction (uRMC) method, utilizing deep learning neural networks, to solve all th...
Efficient model-informed co-segmentation of tumors on PET/CT driven by clustering and classification information.
Computers in biology and medicine
Aug 12, 2024
Automatic tumor segmentation via positron emission tomography (PET) and computed tomography (CT) images plays a critical role in the prevention, diagnosis, and treatment of this disease via radiation oncology. However, segmenting these tumors is chal...
Machine learning predicts conventional imaging metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) using prostate-specific membrane antigen (PSMA) PET radiomics.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jul 31, 2024
PURPOSE: This study investigated imaging biomarkers derived from PSMA-PET acquired pre- and post-metastasis-directed therapy (MDT) to predict 2-year metastasis-free survival (MFS), which provides valuable early response assessment to improve patient ...
Development and validation of a machine learning-based F-fluorodeoxyglucose PET/CT radiomics signature for predicting gastric cancer survival.
Cancer imaging : the official publication of the International Cancer Imaging Society
Jul 30, 2024
BACKGROUND: Survival prognosis of patients with gastric cancer (GC) often influences physicians' choice of their follow-up treatment. This study aimed to develop a positron emission tomography (PET)-based radiomics model combined with clinical tumor-...
F-FDG PET/CT Radiomics-Based Multimodality Fusion Model for Preoperative Individualized Noninvasive Prediction of Peritoneal Metastasis in Advanced Gastric Cancer.
Annals of surgical oncology
Jul 8, 2024
PURPOSE: This study was designed to develop and validate a machine learning-based, multimodality fusion (MMF) model using F-fluorodeoxyglucose (FDG) PET/CT radiomics and kernelled support tensor machine (KSTM), integrated with clinical factors and nu...
Don't Miss the Future of Medicine
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 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- 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 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823