Autors: Ivanova, D. A., Staeva J., Shinkov А., Kovacheva R.
Title: Intelligent EU-TIRADS classificator for early detection of thyroid anomalies using deep learning convolutional neural network
Keywords: Deep Learning, Thyroid Anomalies, CNN

Abstract: The paper presents intelligent EU-TIRADS classificator for early detection of thyroid anomalies using a Deep Learning approach. The image data set is consisting of ultrasound images of the Thyroid glance which are classified in five classes: EU-TIRADS - 1, where 1 represents healthy individuals and EU-TIRADS 2-5, where the stage represents the severity of the disease. The Deep learning approach of choice in this experiment is a Deep learning Convolutional Neural Network. This algorithm was selected as it can provide high accuracy without explicit image processing prior to modelling. Finally, the classification performance metrics are presented.

References

    Issue

    AIP AMEE 2022, vol. 2939, issue 1, pp. Article 020007, 2023, Bulgaria, AIP, DOI 10.1063/5.0185839

    Copyright AIP

    Вид: публикация в международен форум, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus и Web of Science