Quantification of heterogeneity as a biomarker in tumor imaging: a systematic review

L Alic, WJ Niessen, JF Veenland - PloS one, 2014 - journals.plos.org
Background Many techniques are proposed for the quantification of tumor heterogeneity as
an imaging biomarker for differentiation between tumor types, tumor grading, response …

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 …

Thyroid nodule classification in ultrasound images by fine-tuning deep convolutional neural network

J Chi, E Walia, P Babyn, J Wang, G Groot… - Journal of digital …, 2017 - Springer
With many thyroid nodules being incidentally detected, it is important to identify as many
malignant nodules as possible while excluding those that are highly likely to be benign from …

Cascade convolutional neural networks for automatic detection of thyroid nodules in ultrasound images

J Ma, F Wu, T Jiang, J Zhu, D Kong - Medical physics, 2017 - Wiley Online Library
Purpose It is very important for calculation of clinical indices and diagnosis to detect thyroid
nodules from ultrasound images. However, this task is a challenge mainly due to …

Deep convolution neural network for big data medical image classification

R Ashraf, MA Habib, M Akram, MA Latif… - IEEE …, 2020 - ieeexplore.ieee.org
Deep learning is one of the most unexpected machine learning techniques which is being
used in many applications like image classification, image analysis, clinical archives and …

Texture analysis and machine learning to characterize suspected thyroid nodules and differentiated thyroid cancer: Where do we stand?

M Sollini, L Cozzi, A Chiti, M Kirienko - European journal of radiology, 2018 - Elsevier
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 …

Thyroid lesion classification in 242 patient population using Gabor transform features from high resolution ultrasound images

UR Acharya, P Chowriappa, H Fujita, S Bhat… - Knowledge-Based …, 2016 - Elsevier
Thyroid cancer commences from an atypical growth of thyroid tissue at the edge of the
thyroid gland. Initially, it forms a lump in the throat and an over-growth of this tissue leads to …

Fusion of spatial gray level dependency and fractal texture features for the characterization of thyroid lesions

U Raghavendra, UR Acharya, A Gudigar, JH Tan… - Ultrasonics, 2017 - Elsevier
Thyroid is a small gland situated at the anterior side of the neck and one of the largest
glands of the endocrine system. The abrupt cell growth or malignancy in the thyroid gland …

Thyroid nodule recognition using a joint convolutional neural network with information fusion of ultrasound images and radiofrequency data

Z Liu, S Zhong, Q Liu, C **e, Y Dai, C Peng, X Chen… - European …, 2021 - Springer
Objective To develop a deep learning–based method with information fusion of US images
and RF signals for better classification of thyroid nodules (TNs). Methods One hundred sixty …

Automatic recognition and classification system of thyroid nodules in CT images based on CNN

W Li, S Cheng, K Qian, K Yue… - Computational …, 2021 - Wiley Online Library
Thyroid nodule lesions are one of the most common lesions of the thyroid; the incidence rate
has been the highest in the past thirty years. X‐ray computed tomography (CT) plays an …