Automatic Recognition and Classification System of Thyroid Nodules in CT Images Based on CNN
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 increasingly important role in the diagnosis of thyroid diseases. Nonetheless, as a result of the artifact and high comp...
Main Authors: | Wenjun Li, Siyi Cheng, Kai Qian, Keqiang Yue, Hao Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2021-01-01
|
Series: | Computational Intelligence and Neuroscience |
Online Access: | http://dx.doi.org/10.1155/2021/5540186 |
Similar Items
-
CNN models discriminating between pulmonary micro-nodules and non-nodules from CT images
by: Patrice Monkam, et al.
Published: (2018-07-01) -
An Appraisal of Lung Nodules Automatic Classification Algorithms for CT Images
by: Xinqi Wang, et al.
Published: (2019-01-01) -
Automatic Malignant Thyroid Nodule Recognition in Ultrasound Images based on Deep Learning
by: Zhou Meng, et al.
Published: (2020-01-01) -
Automatic thyroid nodule recognition and diagnosis in ultrasound imaging with the YOLOv2 neural network
by: Lei Wang, et al.
Published: (2019-01-01) -
A Framework for Automatic Burn Image Segmentation and Burn Depth Diagnosis Using Deep Learning
by: Hao Liu, et al.
Published: (2021-01-01)