AIMC Topic: Neck

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MUsculo-Skeleton-Aware (MUSA) deep learning for anatomically guided head-and-neck CT deformable registration.

Medical image analysis
Deep-learning-based deformable image registration (DL-DIR) has demonstrated improved accuracy compared to time-consuming non-DL methods across various anatomical sites. However, DL-DIR is still challenging in heterogeneous tissue regions with large d...

ACSwinNet: A Deep Learning-Based Rigid Registration Method for Head-Neck CT-CBCT Images in Image-Guided Radiotherapy.

Sensors (Basel, Switzerland)
Accurate and precise rigid registration between head-neck computed tomography (CT) and cone-beam computed tomography (CBCT) images is crucial for correcting setup errors in image-guided radiotherapy (IGRT) for head and neck tumors. However, conventio...

NABNet: Deep Learning-Based IoT Alert System for Detection of Abnormal Neck Behavior.

Sensors (Basel, Switzerland)
The excessive use of electronic devices for prolonged periods has led to problems such as neck pain and pressure injury in sedentary people. If not detected and corrected early, these issues can cause serious risks to physical health. Detectors for g...

MRI-based deep learning and radiomics for prediction of occult cervical lymph node metastasis and prognosis in early-stage oral and oropharyngeal squamous cell carcinoma: a diagnostic study.

International journal of surgery (London, England)
INTRODUCTION: The incidence of occult cervical lymph node metastases (OCLNM) is reported to be 20-30% in early-stage oral cancer and oropharyngeal cancer. There is a lack of an accurate diagnostic method to predict occult lymph node metastasis and to...

Modeling the Impact of Ergonomic Interventions and Occupational Factors on Work-Related Musculoskeletal Disorders in the Neck of Office Workers with Machine Learning Methods.

Journal of research in health sciences
BACKGROUND: Modeling with methods based on machine learning (ML) and artificial intelligence can help understand the complex relationships between ergonomic risk factors and employee health. The aim of this study was to use ML methods to estimate the...

Image Quality Assessment of a Deep Learning-Based Automatic Bone Removal Algorithm for Cervical CTA.

Journal of computer assisted tomography
BACKGROUND: The present study aims to evaluate the postprocessing image quality of a deep-learning (DL)-based automatic bone removal algorithm in the real clinical practice for cervical computed tomography angiography (CTA).

Automated Segmentation of Lymph Nodes on Neck CT Scans Using Deep Learning.

Journal of imaging informatics in medicine
Early and accurate detection of cervical lymph nodes is essential for the optimal management and staging of patients with head and neck malignancies. Pilot studies have demonstrated the potential for radiomic and artificial intelligence (AI) approach...

Machine learning models based on ultrasound and physical examination for airway assessment.

Revista espanola de anestesiologia y reanimacion
PURPOSE: To demonstrate the utility of machine learning models for predicting difficult airways using clinical and ultrasound parameters.

Deep-learning denoising minimizes radiation exposure in neck CT beyond the limits of conventional reconstruction.

European journal of radiology
BACKGROUND: Neck computed tomography (NCT) is essential for diagnosing suspected neck tumors and abscesses, but radiation exposure can be an issue. In conventional reconstruction techniques, limiting radiation dose comes at the cost of diminished dia...