Artificial intelligence in thyroid ultrasound
CL Cao, QL Li, J Tong, LN Shi, WX Li, Y Xu… - Frontiers in …, 2023 - frontiersin.org
Artificial intelligence (AI), particularly deep learning (DL) algorithms, has demonstrated
remarkable progress in image-recognition tasks, enabling the automatic quantitative …
remarkable progress in image-recognition tasks, enabling the automatic quantitative …
Texture analysis and machine learning to characterize suspected thyroid nodules and differentiated thyroid cancer: Where do we stand?
In thyroid imaging,“texture” refers to the echographic appearence of the parenchyma or a
nodule. However, definition of the image characteristics is operator dependent and …
nodule. However, definition of the image characteristics is operator dependent and …
Utility of a deep-learning algorithm to guide novices to acquire echocardiograms for limited diagnostic use
Importance Artificial intelligence (AI) has been applied to analysis of medical imaging in
recent years, but AI to guide the acquisition of ultrasonography images is a novel area of …
recent years, but AI to guide the acquisition of ultrasonography images is a novel area of …
A novel fusion-based deep learning model for sentiment analysis of COVID-19 tweets
Abstract Undoubtedly, coronavirus (COVID-19) has caused one of the biggest challenges of
all times. The ongoing COVID-19 pandemic has caused more than 150 million infected …
all times. The ongoing COVID-19 pandemic has caused more than 150 million infected …
Ultrasound image-based diagnosis of malignant thyroid nodule using artificial intelligence
Computer-aided diagnosis systems have been developed to assist doctors in diagnosing
thyroid nodules to reduce errors made by traditional diagnosis methods, which are mainly …
thyroid nodules to reduce errors made by traditional diagnosis methods, which are mainly …
Multitask cascade convolution neural networks for automatic thyroid nodule detection and recognition
Thyroid ultrasonography is a widely used clinical technique for nodule diagnosis in thyroid
regions. However, it remains difficult to detect and recognize the nodules due to low …
regions. However, it remains difficult to detect and recognize the nodules due to low …
Artificial intelligence-based thyroid nodule classification using information from spatial and frequency domains
Image-based computer-aided diagnosis (CAD) systems have been developed to assist
doctors in the diagnosis of thyroid cancer using ultrasound thyroid images. However, the …
doctors in the diagnosis of thyroid cancer using ultrasound thyroid images. However, the …
Multi-channel convolutional neural network architectures for thyroid cancer detection
Early detection of malignant thyroid nodules leading to patient-specific treatments can
reduce morbidity and mortality rates. Currently, thyroid specialists use medical images to …
reduce morbidity and mortality rates. Currently, thyroid specialists use medical images to …
Feature extraction using a residual deep convolutional neural network (ResNet-152) and optimized feature dimension reduction for MRI brain tumor classification
S Athisayamani, RS Antonyswamy, V Sarveshwaran… - Diagnostics, 2023 - mdpi.com
One of the top causes of mortality in people globally is a brain tumor. Today, biopsy is
regarded as the cornerstone of cancer diagnosis. However, it faces difficulties, including low …
regarded as the cornerstone of cancer diagnosis. However, it faces difficulties, including low …
Diagnosis of benign and malignant thyroid nodules using combined conventional ultrasound and ultrasound elasticity imaging
P Qin, K Wu, Y Hu, J Zeng… - IEEE journal of biomedical …, 2019 - ieeexplore.ieee.org
Ultrasonography is one of the main imaging methods for diagnosing thyroid nodules.
Automatic differentiation between benign and malignant nodules in ultrasound images can …
Automatic differentiation between benign and malignant nodules in ultrasound images can …