CLASSIFICATION OF ULTRASOUND IMAGES FOR THYROID DETECTION USING SVM
N VIGNESH
, A.MOHAMED ASHFAQ , D DHARANIBALAN , A BHUVANESHWARI , R RADHIGA
Thyroid Ulrasound Images, PCA, GLCM, SVM.
Nowadays the health issue is being worried a lot and so the workload of a doctor becomes comparatively huge. In current scenario, unidentified thyroid has lots of serious medical issues. So, to reduce the workload, the image segmentation and classification of thyroid ultrasound images is most necessary. In our proposed project, the thyroid ultrasound images are taken for further processing. The US images first undergo a pre-processing stage, involving processes like grayscale conversion, intensity calculation and histogram equalization. Most commonly, GLCM algorithm is being used for the segmentation of ultrasound images. The feature output that is obtained is then applied to the PCA as input. All the features extracted from each data are combined into a single matrix for classification with the help of PCA. For classification purposes, The classifier is SVM. In our proposal, classification is done by CNN because SVM is a binary classifier whereas CNN classifier is more efficient compared to SVM.
"CLASSIFICATION OF ULTRASOUND IMAGES FOR THYROID DETECTION USING SVM", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.6, Issue 5, page no.69 - 72, May-2021, Available :https://ijsdr.org/papers/IJSDR2105012.pdf
Volume 6
Issue 5,
May-2021
Pages : 69 - 72
Paper Reg. ID: IJSDR_192962
Published Paper Id: IJSDR2105012
Downloads: 000347218
Research Area: Engineering
Country: PUDUCHERRY, PUDUCHERRY, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
