Automatic Identification of Metastasis in Histopathological Images Using Deep Learning
Daniel de Sousa Luz, Renesio J.O. Costa, Ricardo A. L. Rabêlo, Joel J. P. C. Rodrigues, Flávio H. D. Araújo · 2021
Metastatic tumor is one that spreads from its place of origin to other parts of the body. A tumor formed by metastatic cancer cells is called a metastatic tumor or metastasis. The early identification of these tumors is essential to increase the chances of success in treating the disease. However, for this identification it is necessary to analyze extensive tissues of the affected organs, which is a tiring and error-prone task. In this paper, it is present three deep learning strategies for automatic identification of metastasis in histopathological images. For the development and evaluation of these strategies it was used the PCam database, which is composed of 327,680 color images extracted from histopathological exams of sections of lymph nodes. The obtained results using the fine tuning technique are promising, showing that deep learning models can be used for metastasis identification.