Medical image classification in breast sentinel lymph node detection

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.