AIMC Topic: Head and Neck Neoplasms

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Combining many-objective radiomics and 3D convolutional neural network through evidential reasoning to predict lymph node metastasis in head and neck cancer.

Physics in medicine and biology Mar 29, 2019
Lymph node metastasis (LNM) is a significant prognostic factor in patients with head and neck cancer, and the ability to predict it accurately is essential to optimizing treatment. Positron emission tomography (PET) and computed tomography (CT) imagi...
Neural Networks, Computer Imaging, Three-Dimensional Lymph Nodes Predictive Value of Tests Positron Emission Tomography Computed Tomography Head and Neck Neoplasms Lymphatic Metastasis Humans
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3D radiotherapy dose prediction on head and neck cancer patients with a hierarchically densely connected U-net deep learning architecture.

Physics in medicine and biology Mar 18, 2019
The treatment planning process for patients with head and neck (H&N) cancer is regarded as one of the most complicated due to large target volume, multiple prescription dose levels, and many radiation-sensitive critical structures near the target. Tr...
Aged, 80 and over Young Adult Adult Middle Aged Humans Algorithms Aged Organs at Risk Radiotherapy Dosage Deep Learning Radiotherapy Planning, Computer-Assisted Adolescent Radiotherapy, Intensity-Modulated Head and Neck Neoplasms
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Multi-organ segmentation of the head and neck area: an efficient hierarchical neural networks approach.

International journal of computer assisted radiology and surgery Mar 7, 2019
PURPOSE: In radiation therapy, a key step for a successful cancer treatment is image-based treatment planning. One objective of the planning phase is the fast and accurate segmentation of organs at risk and target structures from medical images. Howe...
Head and Neck Neoplasms Observer Variation Tomography, X-Ray Computed Deep Learning Imaging, Three-Dimensional Humans Neural Networks, Computer
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Deep Learning-Based Delineation of Head and Neck Organs at Risk: Geometric and Dosimetric Evaluation.

International journal of radiation oncology, biology, physics Mar 2, 2019
PURPOSE: Organ-at-risk (OAR) delineation is a key step in treatment planning but can be time consuming, resource intensive, subject to variability, and dependent on anatomical knowledge. We studied deep learning (DL) for automated delineation of mult...
Humans Deep Learning Mouth Parotid Gland Organs at Risk Radiotherapy Planning, Computer-Assisted Head and Neck Neoplasms Esophagus Benchmarking Brain Stem Esophageal Sphincter, Upper Pharyngeal Muscles Larynx Submandibular Gland
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Deep learning in head & neck cancer outcome prediction.

Scientific reports Feb 26, 2019
Traditional radiomics involves the extraction of quantitative texture features from medical images in an attempt to determine correlations with clinical endpoints. We hypothesize that convolutional neural networks (CNNs) could enhance the performance...
Tomography, X-Ray Computed Deep Learning ROC Curve Head and Neck Neoplasms Area Under Curve Humans
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Machine Learning to Predict Delays in Adjuvant Radiation following Surgery for Head and Neck Cancer.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery Jan 29, 2019
OBJECTIVE: To apply a novel methodology with machine learning (ML) to a large national cancer registry to help identify patients who are high risk for delayed adjuvant radiation.
Time-to-Treatment Radiotherapy, Adjuvant Head and Neck Neoplasms Predictive Value of Tests Neoplasm Staging Carcinoma, Squamous Cell Machine Learning Humans United States Aged Algorithms Databases, Factual Socioeconomic Factors Middle Aged Male Female Cohort Studies
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Knowledge-based dose prediction models for head and neck cancer are strongly affected by interorgan dependency and dataset inconsistency.

Medical physics Dec 24, 2018
PURPOSE: The goal of this study was to generate a large treatment plan database for head and neck (H&N) cancer patients that can be considered as the gold standard to train and validate models for knowledge-based (KB) treatment planning and QA. With ...
Radiotherapy Dosage Radiotherapy, Intensity-Modulated Organs at Risk Radiotherapy Planning, Computer-Assisted Humans Quality Assurance, Health Care Databases, Factual Models, Theoretical Tomography, X-Ray Computed Head and Neck Neoplasms Image Processing, Computer-Assisted Knowledge Bases
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AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.

Medical physics Dec 17, 2018
PURPOSE: Radiation therapy (RT) is a common treatment option for head and neck (HaN) cancer. An important step involved in RT planning is the delineation of organs-at-risks (OARs) based on HaN computed tomography (CT). However, manually delineating O...
Humans Time Factors Image Processing, Computer-Assisted Tomography, X-Ray Computed Deep Learning Head and Neck Neoplasms Automation
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Fully convolutional networks in multimodal nonlinear microscopy images for automated detection of head and neck carcinoma: Pilot study.

Head & neck Dec 12, 2018
BACKGROUND: A fully convolutional neural networks (FCN)-based automated image analysis algorithm to discriminate between head and neck cancer and noncancerous epithelium based on nonlinear microscopic images was developed.
Image Processing, Computer-Assisted Spectrum Analysis, Raman Head and Neck Neoplasms Carcinoma, Squamous Cell Algorithms Fluorescence Prospective Studies Humans Pilot Projects Discriminant Analysis Neural Networks, Computer Epithelium Microscopy
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Automatic treatment planning based on three-dimensional dose distribution predicted from deep learning technique.

Medical physics Nov 28, 2018
PURPOSE: To develop an automated treatment planning strategy for external beam intensity-modulated radiation therapy (IMRT), including a deep learning-based three-dimensional (3D) dose prediction and a dose distribution-based plan generation algorith...
Radiation Dosage Humans Head and Neck Neoplasms Radiotherapy Dosage Algorithms Radiotherapy, Intensity-Modulated Radiotherapy Planning, Computer-Assisted Deep Learning Automation
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