IoMT-Based Osteosarcoma Cancer Detection in Histopathology Images Using Transfer Learning Empowered with Blockchain, Fog Computing, and Edge Computing

【Author】 Nasir, Muhammad Umar; Khan, Safiullah; Mehmood, Shahid; Khan, Muhammad Adnan; Rahman, Atta-Ur; Hwang, Seong Oun

【Source】SENSORS

【影响因子】3.847

【Abstract】Bone tumors, such as osteosarcomas, can occur anywhere in the bones, though they usually occur in the extremities of long bones near metaphyseal growth plates. Osteosarcoma is a malignant lesion caused by a malignant osteoid growing from primitive mesenchymal cells. In most cases, osteosarcoma develops as a solitary lesion within the most rapidly growing areas of the long bones in children. The distal femur, proximal tibia, and proximal humerus are the most frequently affected bones, but virtually any bone can be affected. Early detection can reduce mortality rates. Osteosarcoma's manual detection requires expertise, and it can be tedious. With the assistance of modern technology, medical images can now be analyzed and classified automatically, which enables faster and more efficient data processing. A deep learning-based automatic detection system based on whole slide images (WSIs) is presented in this paper to detect osteosarcoma automatically. Experiments conducted on a large dataset of WSIs yielded up to 99.3% accuracy. This model ensures the privacy and integrity of patient information with the implementation of blockchain technology. Utilizing edge computing and fog computing technologies, the model reduces the load on centralized servers and improves efficiency.

【Keywords】blockchain; fog computing; edge computing; osteosarcoma cancer; transfer learning; IoMT

【发表时间】2022 JUL

【收录时间】2022-08-15

【文献类型】实证数据

【主题类别】

区块链应用-实体经济-医疗领域