Year: 2024
Type: article
Abstract: This review explores the landscape of cancer growth detection methodologies utilizing microscopic images.It comprehensively examines diverse approaches, ranging from traditional image processing techniques to cutting-edge machine learning and deep learning algorithms.The review focuses the significance of various image features, including texture, shape, and color, in distinguishing cancerous growth from normal tissue.Emphasizing the need for tailored strategies for different cancer types, the review addresses challenges and opportunities in leveraging microscopic images for precise and early-stage cancer detection.By synthesizing insights from multiple studies, the review provides a holistic overview of the current state of cancer growth detection through microscopic imaging, contributing to the advancement of diagnostic tools and methodologies in oncology.
Authors: Abbirame K.S, Marimuthu Mohana, Sivakumar K
Institution: Dhanalakshmi Srinivasan University
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4401521237