AIMC Topic: Head and Neck Neoplasms
Clear Filters Showing 181 to 190 of 357 articles
Artificial Intelligence in Head and Neck Imaging.
Seminars in ultrasound, CT, and MR
Feb 11, 2022
Artificial intelligence (AI) can be applied to head and neck imaging to augment image quality and various clinical tasks including segmentation of tumor volumes, tumor characterization, tumor prognostication and treatment response, and prediction of ...
Deep learning tools for the cancer clinic: an open-source framework with head and neck contour validation.
Radiation oncology (London, England)
Feb 8, 2022
BACKGROUND: With the rapid growth of deep learning research for medical applications comes the need for clinical personnel to be comfortable and familiar with these techniques. Taking a proven approach, we developed a straightforward open-source fram...
General and custom deep learning autosegmentation models for organs in head and neck, abdomen, and male pelvis.
Medical physics
Feb 7, 2022
PURPOSE: To reduce workload and inconsistencies in organ segmentation for radiation treatment planning, we developed and evaluated general and custom autosegmentation models on computed tomography (CT) for three major tumor sites using a well-establi...
Prospectively-validated deep learning model for segmenting swallowing and chewing structures in CT.
Physics in medicine and biology
Jan 17, 2022
Delineating swallowing and chewing structures aids in radiotherapy (RT) treatment planning to limit dysphagia, trismus, and speech dysfunction. We aim to develop an accurate and efficient method to automate this process.CT scans of 242 head and neck ...
In vivo detection of head and neck tumors by hyperspectral imaging combined with deep learning methods.
Journal of biophotonics
Dec 28, 2021
Currently, there are no fast and accurate screening methods available for head and neck cancer, the eighth most common tumor entity. For this study, we used hyperspectral imaging, an imaging technique for quantitative and objective surface analysis, ...
Deep learning-based automatic delineation of anal cancer gross tumour volume: a multimodality comparison of CT, PET and MRI.
Acta oncologica (Stockholm, Sweden)
Nov 16, 2021
BACKGROUND: Accurate target volume delineation is a prerequisite for high-precision radiotherapy. However, manual delineation is resource-demanding and prone to interobserver variation. An automatic delineation approach could potentially save time an...
Dynamic stochastic deep learning approaches for predicting geometric changes in head and neck cancer.
Physics in medicine and biology
Nov 9, 2021
Modern radiotherapy stands to benefit from the ability to efficiently adapt plans during treatment in response to setup and geometric variations such as those caused by internal organ deformation or tumor shrinkage. A promising strategy is to develop...
The viral expression and immune status in human cancers and insights into novel biomarkers of immunotherapy.
BMC cancer
Nov 5, 2021
BACKGROUND: Viral infections are prevalent in human cancers and they have great diagnostic and theranostic values in clinical practice. Recently, their potential of shaping the tumor immune microenvironment (TIME) has been related to the immunotherap...
Support Vector Machine
DNA, Viral
Epstein-Barr Virus Infections
Herpesvirus 4, Human
Mutation
Leukocytes
Tumor Virus Infections
Papillomavirus Infections
Oncogenic Viruses
Genetic Variation
Kaplan-Meier Estimate
Squamous Cell Carcinoma of Head and Neck
Tumor Microenvironment
Transcriptome
High-Throughput Nucleotide Sequencing
Papillomaviridae
Head and Neck Neoplasms
Biomarkers, Tumor
RNA-Seq
Genome, Viral
Humans
Neoplasms
Immunotherapy
Machine Learning
Stomach Neoplasms
Cascaded deep learning-based auto-segmentation for head and neck cancer patients: Organs at risk on T2-weighted magnetic resonance imaging.
Medical physics
Nov 1, 2021
PURPOSE: To investigate multiple deep learning methods for automated segmentation (auto-segmentation) of the parotid glands, submandibular glands, and level II and level III lymph nodes on magnetic resonance imaging (MRI). Outlining radiosensitive or...
Learning-based synthetic dual energy CT imaging from single energy CT for stopping power ratio calculation in proton radiation therapy.
The British journal of radiology
Oct 28, 2021
OBJECTIVE: Dual energy CT (DECT) has been shown to estimate stopping power ratio (SPR) map with a higher accuracy than conventional single energy CT (SECT) by obtaining the energy dependence of photon interactions. This work presents a learning-based...
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 31984
- Neural Networks, Computer 30211
- Algorithms 27388
- Deep Learning 26888
- Artificial Intelligence 24826
- Robotics 13382
- Image Processing, Computer-Assisted 9732
- Retrospective Studies 9334
- Magnetic Resonance Imaging 6342
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4864
- Support Vector Machine 4766
- Computational Biology 4331
- Brain 4126
- Computer Simulation 3932
Recent Journals
- Scientific reports 6743
- Sensors (Basel, Switzerland) 4794
- PloS one 4196
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1916
- 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 1378
- IEEE journal of biomedical and health informatics 1170
- Journal of chemical information and modeling 1064
- Nature communications 1039
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 873
- Journal of medical Internet research 860
- Briefings in bioinformatics 853