Thyroid

Deep Learning-Based Segmentation of Nodules in Thyroid Ultrasound: Improving Performance by Utilizing Markers Present in the Images.

Computer-aided segmentation of thyroid nodules in ultrasound imaging could assist in their accurate characterization. In this study, using data for 1278 nodules, we proposed and evaluated two methods for deep learning-based segmentation of thyroid nodules that utilize calipers present in the images. The first method used approximate nodule masks generated based on the calipers. The second method c...

Cascade and Fusion of Multitask Convolutional Neural Networks for Detection of Thyroid Nodules in Contrast-Enhanced CT.

With the development of computed tomography (CT), the contrast-enhanced CT scan is widely used in the diagnosis of thyroid nodules. However, due to the artifacts and high complexity of thyroid CT images, traditional machine learning has difficulty in detecting thyroid nodules in contrast-enhanced CT. A fully automated detection algorithm for thyroid nodules using contrast-enhanced CT images is dev...

Classification and Diagnosis of Thyroid Carcinoma Using Reinforcement Residual Network with Visual Attention Mechanisms in Ultrasound Images.

How to differentiate thyroid cancer nodules from a large number of benign nodules is always a challenging subject for clinicians. This paper proposes ...

Radiation-Induced Hypothyroidism After Radical Intensity Modulated Radiation Therapy for Oropharyngeal Carcinoma.

PURPOSE: To evaluate 2 published normal tissue complication probability models for radiation-induced hypothyroidism (RHT) on a large cohort of orophar...

Automated detection and classification of thyroid nodules in ultrasound images using clinical-knowledge-guided convolutional neural networks.

Accurate diagnosis of thyroid nodules using ultrasonography is a valuable but tough task even for experienced radiologists, considering both benign an...

NOVEL MUTATIONS IN AN INFANT WITH MICROCEPHALIC PRIMORDIAL DWARFISM, DILATED CARDIOMYOPATHY, SUBCLINICAL HYPOTHYROIDISM, AND EARLY DEATH: EXPANDING THE PHENOTYPE OF MUTATIONS.

OBJECTIVE: Microcephalic primordial dwarfism (MPD) is a group of clinically and genetically heterogeneous disorders which result in severe prenatal an...

Prediction of Immunohistochemistry of Suspected Thyroid Nodules by Use of Machine Learning-Based Radiomics.

The purpose of this study was to develop and validate a radiomics model for evaluating immunohistochemical characteristics in patients with suspected...

Management of Thyroid Nodules Seen on US Images: Deep Learning May Match Performance of Radiologists.

BackgroundManagement of thyroid nodules may be inconsistent between different observers and time consuming for radiologists. An artificial intelligenc...

Assessment of risk based on variant pathways and establishment of an artificial neural network model of thyroid cancer.

BACKGROUND: This study aimed to establish an artificial neural network (ANN) model based on variant pathways to predict the risk of thyroid cancer.

Using Artificial Intelligence to Revise ACR TI-RADS Risk Stratification of Thyroid Nodules: Diagnostic Accuracy and Utility.

Background Risk stratification systems for thyroid nodules are often complicated and affected by low specificity. Continual improvement of these syste...

High-Resolution Raman Microscopic Detection of Follicular Thyroid Cancer Cells with Unsupervised Machine Learning.

We use Raman microscopic images with high spatial and spectral resolution to investigate differences between human follicular thyroid (Nthy-ori 3-1) a...

Comparison of robot-assisted modified radical neck dissection using a bilateral axillary breast approach with a conventional open procedure after propensity score matching.

BACKGROUND: There is ongoing debate about whether or not robot-assisted thyroidectomy is appropriate for modified radical neck dissection (MRND). The ...

To Generate an Ensemble Model for Women Thyroid Prediction Using Data Mining Techniques.

Objective: The main objective of this paper is to easily identify thyroid symptom for treatment. Methods: In this paper two main techniques are propos...

Machine Learning Approach to find the relation between Endometriosis, benign breast disease, cystitis and non-toxic goiter.

The exact mechanism of endometriosis is unknown. The recommendation system (RS) based on item similarities of machine learning has never been applied ...

Adaptive multi-view multi-label learning for identifying disease-associated candidate miRNAs.

Increasing evidence has indicated that microRNAs(miRNAs) play vital roles in various pathological processes and thus are closely related with many com...

Evolution Strategies in Transaxillary Robotic Thyroidectomy: Considerations on the First 449 Cases Performed.

BACKGROUND: In the past 20 years, the fast spread of new surgical technologies has reached an important peak with the advent of the robotic surgery. M...

Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT.

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...

[Robot-assisted transaxillary thyroid surgery; 5 years later].

Five years ago, robot-assisted transaxillary thyroidectomy (RATT) was introduced in the Netherlands. The major advantage of this technique, when compa...

Detecting abnormal thyroid cartilages on CT using deep learning.

PURPOSE: The purpose of this study was to evaluate the performance of a deep learning algorithm in detecting abnormalities of thyroid cartilage from c...

Deep convolutional neural network for the diagnosis of thyroid nodules on ultrasound.

BACKGROUND: We designed a deep convolutional neural network (CNN) to diagnose thyroid malignancy on ultrasound (US) and compared the diagnostic perfor...