Advancements in Medical Image Analysis: A Comprehensive Method of AI-Based Classification and Segmentation Technique

Abstract

Medical imaging is an important tool in the current healthcare system for precise diagnosis and treatment of a wide variety of illnesses. The use of artificial intelligence, namely machine learning and deep learning approaches, has transformed medical picture interpretation and resulted in substantial advances in the area. This research looks at the most recent advances in artificial intelligence as they pertain to medical image processing, with a focus on the classification and segmentation of ocular problems. Given the rising frequency of eye diseases and the imperative need for early diagnosis, artificial intelligence (AI) presents a potential approach for automated, precise, and early detection of diverse ocular issues. The article discusses the most recent methodologies, challenges, and possible applications in the field of AI-driven segmentation and classification of ocular diseases utilizing medical imaging.

Received: 19 November 2023 | Revised: 7 March 2024 | Accepted: 23 April 2024

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

The data that support the findings of this study are openly available in public repository as cited and also available on request from the corresponding author upon reasonable request.

Author Contribution Statement

Ankur Biswas: Conceptualization, Methodology, Software, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Visualization, Supervision, Project administration, Funding acquisition. Rita Banik: Methodology, Investigation, Visualization, Supervision, Project administration, Funding acquisition.