AIMC Topic: Thyroid Gland

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Tracked 3D ultrasound and deep neural network-based thyroid segmentation reduce interobserver variability in thyroid volumetry.

PloS one
Thyroid volumetry is crucial in the diagnosis, treatment, and monitoring of thyroid diseases. However, conventional thyroid volumetry with 2D ultrasound is highly operator-dependent. This study compares 2D and tracked 3D ultrasound with an automatic ...

Conversion rates in robotic thyroid surgery: A systematic review and meta-analysis.

The international journal of medical robotics + computer assisted surgery : MRCAS
OBJECTIVE: To define the conversion risk to open procedure during robot-assisted thyroid surgery (RATS) identifying potential specific subclasses of procedures or accesses at higher conversion risk.

Feature discretization-based deep clustering for thyroid ultrasound image feature extraction.

Computers in biology and medicine
Ultrasound imaging technology has the advantage of being convenient, less harmful and widely applied, making ultrasonography one of the most popular methods for disease diagnosis. With the rapid development of Computer- Aided Diagnosis (CAD) technolo...

Thyroid endocrine disruption and hepatotoxicity induced by bisphenol AF: Integrated zebrafish embryotoxicity test and deep learning.

The Science of the total environment
Bisphenol AF (BPAF) is an emerging contaminant prevalent in the environment as one of main substitutes of bisphenol A (BPA). It was found that BPAF exhibited estrogenic effects in zebrafish larvae in our previous study, while little is known about it...

Ambiguous and Incomplete: Natural Language Processing Reveals Problematic Reporting Styles in Thyroid Ultrasound Reports.

Methods of information in medicine
OBJECTIVE: Natural language processing (NLP) systems convert unstructured text into analyzable data. Here, we describe the performance measures of NLP to capture granular details on nodules from thyroid ultrasound (US) reports and reveal critical iss...

Deep learning-based ultrasonic dynamic video detection and segmentation of thyroid gland and its surrounding cervical soft tissues.

Medical physics
BACKGROUND: The prevalence of thyroid diseases has been increasing year by year. In this study, we established and validated a deep learning method (Cascade region-based convolutional neural network, R-CNN) based on ultrasound videos for automatic de...

Artificial Intelligence in Toxicological Pathology: Quantitative Evaluation of Compound-Induced Follicular Cell Hypertrophy in Rat Thyroid Gland Using Deep Learning Models.

Toxicologic pathology
Digital pathology has recently been more broadly deployed, fueling artificial intelligence (AI) application development and more systematic use of image analysis. Here, two different AI models were developed to evaluate follicular cell hypertrophy in...

Using deep learning to identify the recurrent laryngeal nerve during thyroidectomy.

Scientific reports
Surgeons must visually distinguish soft-tissues, such as nerves, from surrounding anatomy to prevent complications and optimize patient outcomes. An accurate nerve segmentation and analysis tool could provide useful insight for surgical decision-maki...

Non-invasive thyroid detection based on electroglottogram signal using machine learning classifiers.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Thyroid is a butterfly shaped gland located in the neck region. Hormones are secreted by the thyroid gland that is responsible for various functions that maintain metabolism of the body. The variance in secretion of the hormones causes disorders such...

Recognition of Thyroid Ultrasound Standard Plane Images Based on Residual Network.

Computational intelligence and neuroscience
Ultrasound is one of the critical methods for diagnosis and treatment in thyroid examination. In clinical application, many reasons, such as large outpatient traffic, time-consuming training of sonographers, and uneven professional level of physician...