Texture Identification of Cancer Cell Using Tamura’s Feature for Precise Treatment to Avoid Metastasis: A New Era of Artificial Intelligence in Healthcare Industry 5.0

Soumen Santra

¹ Research Scholar, Department of CSE, Maulana Abul Kalam Azad University of Technology, West Bengal, India

Email: [email protected] 

² Assistant Professor, Department of MCA, Techno International New Town, West Bengal, India

Email: [email protected]

³ Associate Professor, Department of MCA, Techno International New Town, West Bengal, India

Email: [email protected]

⁴ Professor, Dept. of CSE, RCC Institute of Information Technology, Kolkata, West Bengal, India

Email: [email protected]

⁵ Associate Professor, Dept. of ECE, B.P. Poddar Institute of Management & Technology, Kolkata, West Bengal, India

Email: [email protected]

*Corresponding Author: Soumen Santra, Email: [email protected]

Texture plays a significant role in image processing where the images are computed to detect mortal diseases like cancer. Artificial Intelligence (AI) finds various approaches in the level of industry expert 5.0 for the precise treatment of this disease which helps to motivate and inculcate patient’s mind from the darkness of it. Cancer changes the structure of the affected area (cell and/or tissue and/or organ) in an irregular manner so the texture or coarseness of ROI (Region of Interest) changes rapidly in the patient’s body. Tamura’s feature is playing to detect different assessment parameters like linelikeness, coarseness, direction of texture, body roughness, smoothness, irregularity, contrast by which the model can assess whether a ROI of input dataset carcinogenic or not. This communication has detected the precise condition of the image of the affected area which helps medical practioner for proper diagnose and treatment to avoid metastasis. Here we use python 3.7 in Google Colab platform to execute the model. As the model is based on deep learning methodologies so this cloud platform helps us to reduce the computation time for big dataset.

Machine Learning, Image Processing, Software as a Service, Carcinoma, Breast Cancer

Soumen Santra, Hemanta Dey, Ammlan Ghosh, Dipankar Majumdar, Surajit Mandal (2024). Texture Identification of Cancer Cell Using Tamura’s Feature for Precise Treatment to Avoid Metastasis: A new Era of Artificial Intelligence in Healthcare Industry 5.0. Journal of Artificial Intelligence and Systems, 6, 76–84. https://doi.org/10.33969/AIS.2024060105.

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