Artificial neural network model to distinguish follicular adenoma from follicular carcinoma on fine needle aspiration of thyroid.

Journal: Diagnostic cytopathology

Published Date: Dec 20, 2017

Abstract

BACKGROUND: To distinguish follicular adenoma (FA) and follicular carcinoma (FC) of thyroid in fine needle aspiration cytology (FNAC) is a challenging problem.

Authors

Rajiv Savala

Department of Pathology, Postgraduate Institute of Medical Education and Research, Chandigarh, India.
Pranab Dey

Department of Cytology, Post Graduate Institute of Medical Education and Research, Chandigarh, India.
Nalini Gupta

Department of Cytology, Post Graduate Institute of Medical Education and Research, Chandigarh, India.

Keywords

Adenocarcinoma, Follicular Adenoma Biopsy, Fine-Needle Cell Nucleus Diagnosis, Differential Humans Neural Networks, Computer Thyroid Gland Thyroid Neoplasms

External Resources

View on PubMed Access via DOI PubMed (29266871)

Artificial neural network model to distinguish follicular adenoma from follicular carcinoma on fine needle aspiration of thyroid.

Abstract

Authors

Keywords

External Resources

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