International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Survey on Breast Cancer analysis

Author(s) Shruthi G K, Dr. Pushpa Ravikumar
Country India
Abstract Breast cancer constitutes 12% of all newly diagnosed cases globally, making it the most predominant type of cancer as a whole. Histopathology images, among all the medical image modalities, maintain the cancer's path and provide richer phenotypic relevant information. The patient's immune system is progressively predictable as a critical feature in defining the suitable treatment. Tumor-infiltrating lymphocytes (TILs), immune cells found within tumors, are emerging as key biomarkers in breast cancer. The detection of lymph node metastasis affects the management of patients with primary breast cancer significantly in terms of staging, treatment, and prognosis.Tumoour infiltrating lymphocytes score and lymph node metastasis identification plays a very important role in staging of breast cancer.This review aims to provide a comprehensive overview on how deep learning-based method is used to compute the Tumour-Infiltrating Lymphocytes (TILs) score and lymph node metastasis from breast cancer histopathological images.
Keywords Index Terms—Breast cancer, T-lymphocytes, lymph node metastasis, Image Processing, CNN, Deep Learning.
Field Engineering
Published In Volume 6, Issue 5, September-October 2024
Published On 2024-10-29
Cite This Survey on Breast Cancer analysis - Shruthi G K, Dr. Pushpa Ravikumar - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.28628
DOI https://doi.org/10.36948/ijfmr.2024.v06i05.28628
Short DOI https://doi.org/g8pnq9
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