UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 8 Issue 7
July-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

Unique Identifier

Published Paper ID:
JETIR2107743


Registration ID:
313299

Page Number

g96-g100

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Title

Thyroid Malignancy Detection

Abstract

Thyroid Cancer is highly fatal and often diagnosis is time consuming due to the requirement of multiple tests and biopsies. In this project, this observation has been taken into consideration and a technique has been proposed that will present a more objective and accurate classification and would further offer a valuable second opinion to medical practitioners. A classifier is used that extracts features that quantify changes in the texture of the training images from both benign and malignant nodules. The resulting feature vectors are used to train the classifier. A VGG-16 model that is pre-trained on the ImageNet dataset is fine tuned using thyroid ultrasound images to classify malignant and benign lesions. This system is expected to be fast while being accurate at the same time in order to be useful in scenarios requiring speedy diagnosis and treatment.

Key Words

Thyroid Malignancy, Deep Learning, Convolutional Neural Networks, Transfer Learning

Cite This Article

"Thyroid Malignancy Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 7, page no.g96-g100, July-2021, Available :http://www.jetir.org/papers/JETIR2107743.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Thyroid Malignancy Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 7, page no. ppg96-g100, July-2021, Available at : http://www.jetir.org/papers/JETIR2107743.pdf

Publication Details

Published Paper ID: JETIR2107743
Registration ID: 313299
Published In: Volume 8 | Issue 7 | Year July-2021
DOI (Digital Object Identifier):
Page No: g96-g100
Country: Pune, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162


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