Osteosarcoma is a common type of cancer that occurs in the cells and spreads to the bones. Osteosarcoma can develop due to genetic mutations, but most cases are not inherited. It often starts at the ends of long bones in the arms and legs during periods of rapid growth. Osteosarcoma can be diagnosed by Histopathological examination using microscopic images. In recent trends, pathological images are increasingly being examined by computer-intelligent approaches, also known as computational pathology. This field utilizes machine learning and deep learning algorithms to analyze digital pathology slides. Histopathology image-based osteosarcoma detection is not the subject of any review papers. So, this study examines historical and current literature to present a concise review of Histopathology image-based Osteosarcoma detection. This review discussed the types, clinical diagnosis, and modern and future treatment methods of Osteosarcoma. Also, a review of machine learning (ML) and deep learning (DL) approaches for histopathology image osteosarcoma detection is analyzed. Sophisticated methods and the future scope of osteosarcoma detection have also been discussed. Comparative analysis and results of reviewed papers were also analyzed in this review study. This article aims to generate fresh concepts for creating more potent treatment alternatives. © 2025 Elsevier B.V., All rights reserved.