Sentinel Lymph Node (SLN) Metastases in Breast Carcinoma Whole Slide Image (WSI) through Densenet Deep Learning Network: An Approach towards Clinical Management and Treatment

Abstract

This paper envisions a new and faster sentinel lymph metastases classification model which will help the pathology experts to perform fast and accurate diagnosis. This paper discussed a CNN based image classification model, to classify breast lymph node metastasis from WSI images, called DenseNet-161. Breast cancer intends to spread throughout the body. Cancer cells spread locally by infecting nearby healthy tissue. And it can spread throughout a region by infecting adjacent lymph nodes, tissues, or organs. CNN model initially learns the features from the training data. Subsequently after fitting the training data well it tries to generalize and make accurate predictions for the incoming new data which it has not seen earlier. Overfitting refers to a model that models the training data too well. The noise persists even after using the thresholding pre-processing strategy, necessitating extra pre-processing before training the model. Furthermore, increasing the dataset size by data-augmentation will significantly increase the accuracy.