AIMC Topic: Head and Neck Neoplasms

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The robotic-assisted extended "Sistrunk" approach for tumors of the upper aerodigestive tract with limited transoral access: First description of oncological and functional outcomes.

Head & neck Jun 2, 2022
We report on the first clinical experience with the robotic-assisted extended "Sistrunk" approach (RESA) for access to constrained spaces of the upper aerodigestive tract. This prospective case cohort study include six patients that underwent RESA if...
Robotics Robotic Surgical Procedures Margins of Excision Cohort Studies Head and Neck Neoplasms Humans
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A deep learning-based radiomics approach to predict head and neck tumor regression for adaptive radiotherapy.

Scientific reports May 27, 2022
Early regression-the regression in tumor volume during the initial phase of radiotherapy (approximately 2 weeks after treatment initiation)-is a common occurrence during radiotherapy. This rapid radiation-induced tumor regression may alter target coo...
Head and Neck Neoplasms Neural Networks, Computer Radiation Injuries Tomography, X-Ray Computed Deep Learning Humans
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Tackling the class imbalance problem of deep learning-based head and neck organ segmentation.

International journal of computer assisted radiology and surgery May 16, 2022
PURPOSE: The segmentation of organs at risk (OAR) is a required precondition for the cancer treatment with image- guided radiation therapy. The automation of the segmentation task is therefore of high clinical relevance. Deep learning (DL)-based medi...
Head and Neck Neoplasms Neural Networks, Computer Tomography, X-Ray Computed Organs at Risk Humans Radiotherapy, Image-Guided Deep Learning Image Processing, Computer-Assisted
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Histopathology-Based Diagnosis of Oral Squamous Cell Carcinoma Using Deep Learning.

Journal of dental research Apr 21, 2022
Oral squamous cell carcinoma (OSCC) is prevalent around the world and is associated with poor prognosis. OSCC is typically diagnosed from tissue biopsy sections by pathologists who rely on their empirical experience. Deep learning models may improve ...
Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Mouth Neoplasms Humans Carcinoma, Squamous Cell Deep Learning
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Use of deep learning to predict the need for aggressive nutritional supplementation during head and neck radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Apr 21, 2022
PURPOSE/OBJECTIVES: Radiation therapy (RT) for the treatment of patients with head and neck cancer (HNC) leads to side effects that can limit a person's oral intake. Early identification of patients who need aggressive nutrition supplementation via a...
Head and Neck Neoplasms Dietary Supplements Humans Neural Networks, Computer Deep Learning Cone-Beam Computed Tomography Artificial Intelligence
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Decentralized Distributed Multi-institutional PET Image Segmentation Using a Federated Deep Learning Framework.

Clinical nuclear medicine Apr 20, 2022
PURPOSE: The generalizability and trustworthiness of deep learning (DL)-based algorithms depend on the size and heterogeneity of training datasets. However, because of patient privacy concerns and ethical and legal issues, sharing medical images betw...
Head and Neck Neoplasms Positron-Emission Tomography Deep Learning Image Processing, Computer-Assisted Humans Algorithms
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Pseudo low-energy monochromatic imaging of head and neck cancers: Deep learning image reconstruction with dual-energy CT.

International journal of computer assisted radiology and surgery Apr 12, 2022
PURPOSE: Low-energy virtual monochromatic images (VMIs) derived from dual-energy computed tomography (DECT) systems improve lesion conspicuity of head and neck cancer over single-energy CT (SECT). However, DECT systems are installed in a limited numb...
Humans Deep Learning Image Processing, Computer-Assisted Head and Neck Neoplasms Retrospective Studies Tomography, X-Ray Computed Radiography, Dual-Energy Scanned Projection
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Head and neck synthetic CT generated from ultra-low-dose cone-beam CT following Image Gently Protocol using deep neural network.

Medical physics Mar 14, 2022
PURPOSE: Image guidance is used to improve the accuracy of radiation therapy delivery but results in increased dose to patients. This is of particular concern in children who need be treated per Pediatric Image Gently Protocols due to long-term risks...
Humans Retrospective Studies Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted Head and Neck Neoplasms Child Radiotherapy Planning, Computer-Assisted Cone-Beam Computed Tomography
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Deep learning-based auto segmentation using generative adversarial network on magnetic resonance images obtained for head and neck cancer patients.

Journal of applied clinical medical physics Mar 9, 2022
PURPOSE: Adaptive radiotherapy requires auto-segmentation in patients with head and neck (HN) cancer. In the current study, we propose an auto-segmentation model using a generative adversarial network (GAN) on magnetic resonance (MR) images of HN can...
Organs at Risk Image Processing, Computer-Assisted Head and Neck Neoplasms Magnetic Resonance Imaging Humans Deep Learning
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Cross-institutional outcome prediction for head and neck cancer patients using self-attention neural networks.

Scientific reports Feb 24, 2022
In radiation oncology, predicting patient risk stratification allows specialization of therapy intensification as well as selecting between systemic and regional treatments, all of which helps to improve patient outcome and quality of life. Deep lear...
Quality of Life Carcinoma, Squamous Cell Diagnosis, Computer-Assisted Aged Prognosis Deep Learning Humans Adult Male Retrospective Studies Neural Networks, Computer Aged, 80 and over Biomarkers, Tumor Middle Aged Female Positron Emission Tomography Computed Tomography Image Processing, Computer-Assisted Neoplasm Recurrence, Local Head and Neck Neoplasms Attention
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