Please use this identifier to cite or link to this item:
|Title:||Transfer learning for breast cancer classification using small dataset of ultrasound images|
|Publisher:||Institute of Electrical and Electronics Engineers Inc.|
|Abstract:||Globally Breast cancer has been identified as probably the most deadly type of cancer among women. This proposed work implements a sophisticated Breast Cancer Prognosis from Ultrasound Dataset using Transfer Learning. The two great challenges for the Researchers are Breast cancer analysis and the Prognosis. Malignancy patients are influenced by many aspects. All these factors and the outward symptoms in the individual are recorded making use of scanning devices such as Ultrasound pictures, histopathology, cytology, mammogram, etc. After that this data has been used for the medical diagnosis of cancer utilizing the Transfer learning method. This paper aims to compare & analyze our suggested model Transfer learning and deep learning techniques for Breast cancer Recognition from Ultrasound images predicated on parameters viz. Accuracy, Precision, Losses, Recall, and Area under Curve (AUC). The outcome of the proposed method results in best accuracy and obtains minimum losses when dealing with machine learning and deep learning approaches for the diagnosis of breast cancer in Ultrasound Images.|
|Appears in Collections:||Conferences|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.