Medical image classification in breast sentinel lymph node detection
Department of Disease Control, School of Veternary Medicine, University of Zambia, Lusaka, Zambia.
Review
World Journal of Biology Pharmacy and Health Sciences, 2023, 14(01), 015–019.
Article DOI: 10.30574/wjbphs.2023.14.1.0153
Publication history:
Received on 23 February 2023; revised on 31 March 2023; accepted on 03 April 2023
Abstract:
With the advent of computational imaging technologies, machine learning now provides an essential supporting modeling tool for disease detection. Breast Sentinel Lymph Node detection requires medical image classification from Raman spectral image dataset. This is achieved with a convolutional neural network, a machine learning technique.
The current efforts on this literature review aim to explore a branch of deep- learning for the detection of first breast cancerous lymph node from Raman Spectroscopy Probe. With this technique, we evaluate the use of a convolutional neural network, a type of machine learning- based algorithm, used to automatically detect cancer metastases in lymph nodes with high accuracy from trained Raman Spectral Dataset.
Keywords:
Machine learning; Convolutional Neural Network; Breast Sentinel Lymph Node; Raman Spectroscopy
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0