Muscle fat infiltration (MFI) of the deep cervical spine extensors has been observed in cervical spine conditions using time-consuming and rater-dependent manual techniques. Deep learning convolutional neural network (CNN) models have demonstrated st...
OBJECTIVES: This study was conducted in order to evaluate a novel risk stratification model using dual-energy CT (DECT) texture analysis of head and neck squamous cell carcinoma (HNSCC) with machine learning to (1) predict associated cervical lymphad...
PURPOSE: To develop a deep learning-based computer-aided diagnosis (CAD) system for use in the CT diagnosis of cervical lymph node metastasis (LNM) in patients with thyroid cancer.
Computer methods and programs in biomedicine
Mar 28, 2018
BACKGROUND AND OBJECTIVE: Relative location prediction in computed tomography (CT) scan images is a challenging problem. Many traditional machine learning methods have been applied in attempts to alleviate this problem. However, the accuracy and spee...
Accumulation of head impacts may contribute to acute and long-term brain trauma. Wearable sensors can measure impact exposure, yet current sensors do not have validated impact detection methods for accurate exposure monitoring. Here we demonstrate a ...
Background/aim: Primary hyperparathyroidism (PHPT) is characterized by increased calcium (Ca) and parathyroid hormone (PTH) levels. Surgical removal of the culprit hyperfunctioning parathyroid gland is the preferred treatment. In this study, we aimed...
PURPOSE: A critical step in adaptive radiotherapy (ART) workflow is deformably registering the simulation CT with the daily or weekly volumetric imaging. Quantifying the deformable image registration accuracy under these circumstances is a complex ta...
BACKGROUND: Cystic hygroma is a rare benign abnormality of the lymphatic system generally occurring in young children less than 2 years old. The standard transcervical surgical treatment of cystic hygroma may often leave a permanent scar in the neck ...
OBJECTIVE: To compare the quality of deep learning-reconstructed turbo spin-echo (DL-TSE) and conventionally interpolated turbo spin-echo (Conv-TSE) techniques in contrast-enhanced MRI of the neck.
Shanghai kou qiang yi xue = Shanghai journal of stomatology
Dec 1, 2024
PURPOSE: To investigate the value of machine learning model based on enhanced CT imaging features and clinical parameters in predicting cervical lymph node metastasis in patients with tongue squamous cell carcinoma (TSCC).