Towards professionally user-adaptive large medical image transmission processing in mobile telemedicine systems

To effectively and efficiently reduce the transmission costs of large medical image in (mobile) telemedicine systems, we design and implement a professionally user-adaptive large medical image transmission method called UMIT. Before transmission, a preprocessing step is first conducted to obtain the optimal image block (IB) replicas based on the users' professional preference model and the network bandwidth at a master node. After that, the candidate IBs are transmitted via slave nodes according to the transmission priorities. Finally, the IBs can be reconstructed and displayed at the users' devices. The proposed method includes three enabling techniques: (1) user's preference degree derivation of the medically useful areas, (2) an optimal IB replica storage scheme, and (3) an adaptive and robust multi-resolution-based IB replica selection and transmission method. The experimental results show that the performance of our proposed UMIT method is both efficient and effective, minimizing the response time by decreasing the network transmission cost.