Detection of Thyroid Nodules Through Neural Networks and Processing of Echographic Images
| Autor: | Eddie E. Galarza, Nancy E. Guerrón, Julio C. Toalombo, Alex R. Haro |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Thyroid nodules
Artificial neural network Computer science business.industry Free access Pattern recognition Python (programming language) medicine.disease Convolutional neural network 030218 nuclear medicine & medical imaging 03 medical and health sciences Identification (information) 0302 clinical medicine Software medicine Preprocessor Artificial intelligence business computer 030217 neurology & neurosurgery computer.programming_language |
| Zdroj: | Computational Science and Its Applications – ICCSA 2020 ISBN: 9783030588106 ICCSA (4) |
| DOI: | 10.1007/978-3-030-58811-3_12 |
| Popis: | The abnormal functioning of hormones produces the appearance of malformations in human bodies that must be detected early. In this manuscript, two proposals are presented for the identification of thyroid nodules in ultrasound images, using convolutional neural networks. For the network training, 400 images obtained from a medical center and stored in a database have been used. Free access software (Python and TensorFlow) has been used as part of the algorithm development, following the stages of image preprocessing, network training, filtering and layer construction. Results graphically present the incidence of people suffering from this health problem. In addition, based on the respective tests, it is identified that the system developed in Python has greater precision and accuracy, 90% and 81% respectively, than TensorFlow design. Through neural networks, the recognition up to 4 mm thyroid nodules is evidenced. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|