Abstract | An abnormal growth develop in female uterus is uterus fibroids. Sometimes these fibroids may cause severe problems like miscarriage. If this fibroids are not detected it ultimately grows in size and numbers. Among different image modalities, ultrasound is more efficient to detect uterus fibroids. This paper proposes a model in deep learning for fibroid detection with many advantages. The proposed deep learning model overpowers the drawbacks of the existing methodologies of fibroid detection in all stages like noise removal, contrast enhancement, Classification. The preprocessed image is classified into two classes of data: fibroid and non-fibroid, which is done using the MBFCDNN method. The method is validated using the parameters Sensitivity, specificity, accuracy, precision, F-measure. It is found that the sensitivity is 94.44%, specificity 95 % and accuracy 94.736%. |
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