Skeletal Bone Age Classification Using Svm
Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 3
Abstract
Bone Age Assessment (Baa) Is A Method Of Evaluating The Level Of Skeletal Maturation In Children. The Manual Methods Are Prone To The Variability Of Observation, Time-Consuming And Limited To Objective Decisions. Baa Is Purely Based On Measuring The Length And Shape Of Various Bones, So Radiographs Images Are A Must. In This Research Work, A Multi-Scale Structuring Element Is Used To Enhance The X-Ray Of A Left Hand-Wrist Using Circular Shape Structuring Element At Different Scales To Extract Bright And Dark Portions At All Scales And Its Neighboring Scales. The Deep Learning And Neural Network Methods Are Justifiable To Implement When There Is A Large Amount Of Data And Hardware Resources Are Sufficient. But , In Cases When Data Size Is Small And Resources Are Less There Is Need To Find An Accurate Algorithm That Can Work On Small Unimodal Data And Requires Minimum Resources .This Research Work Focuses On Finding An Algorithm That Produces High Accuracy And Low Misclassification Error . The Results Show That Knn And Svm Seem To Fit Into Such Condition As They Have Good Accuracy As Compared To Naïve Bayes .
Authors and Affiliations
Amandeep Kaur, Kulvinder S. Mann
Keywords
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