What is it about?
Computer Aided Diagnosis (CAD) in ultrasound (US) imaging of benign and malignant thyroid nodules.
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Why is it important?
• Random Forests were used for the patch-based classification of thyroid nodules and its performance was compared with the SVM classifier. • Random Forests classify malignant and benign nodules with ROC AUC = 0.971 when using all patches and ROC AUC = 0.999 when using 75% of all patches. • A new patch-based features extraction technique based on Two-Threshold Binary Decomposition is used for diagnosis of thyroid nodules. • Data from two different ultrasound devices was used in the study. • Patch-based classification operates with small squares of thyroid image measuring just 17 × 17 px, providing promisingly accurate results.
Perspectives
An interesting paper regarding the future of Computer Aided Diagnosis (CAD) and its future role in clinical medicine.
Mr Sumeet Gulati
International Clinical Research Center, St. Anne’s University Hospital Brno, Pekarska 53, 656 91, Brno, Czech Republic
Read the Original
This page is a summary of: Patch-based classification of thyroid nodules in ultrasound images using direction independent features extracted by two-threshold binary decomposition, Computerized Medical Imaging and Graphics, January 2019, Elsevier,
DOI: 10.1016/j.compmedimag.2018.10.001.
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