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

This research proposes a novel sentinel lymph metastasis categorization methodology that will aid pathologists in making quick and accurate diagnoses. DenseNet-161, a CNN-based image classification model for classifying breast lymph node metastases from WSI images, was discussed in this study. Breast cancer has the intention of spreading throughout the body. Locally, cancer cells spread by infecting healthy tissue nearby. It can also spread throughout an area by infecting nearby lymph nodes, tissues, or organs. The CNN model learns the features from the training data at first. Following that, after successfully fitting the training data, it attempts to generalise and generate correct predictions for new data that it has not seen before. A model that overfits the training data is referred to as overfitting. Even after applying the thresholding pre-processing technique, the noise persists, necessitating additional pre-processing before training the model. Furthermore, data-augmentation will considerably improve the accuracy by expanding the dataset size.

Author(S) Details

Rajasekaran Subramanian
Keshav Memorial Institute of Technology, Hyderabad, Telangana, India.

R. Devika Rubi
Keshav Memorial Institute of Technology, Hyderabad, Telangana, India.

Abhay Krishna Kasavaraju
Keshav Memorial Institute of Technology, Hyderabad, Telangana, India.

Samayk Jain
Keshav Memorial Institute of Technology, Hyderabad, Telangana, India.

Swathi Guptha
Keshav Memorial Institute of Technology, Hyderabad, Telangana, India.

Suraj Raghavendra Pingali
Keshav Memorial Institute of Technology, Hyderabad, Telangana, India.

View Book:- https://stm.bookpi.org/IDMMR-V5/article/view/5913