Progressive Batch Medical Image Retrieval Processing in Mobile Wireless Networks

This article addresses a multi-query optimization problem for distributed medical image retrieval in mobile wireless networks by exploiting the dependencies in the derivation of a retrieval evaluation plan. To the best of our knowledge, this is the first work investigating batch medical image retrieval (BMIR) processing in a mobile wireless network environment. Four steps are incorporated in our BMIR algorithm. First, when a number of retrieval requests (i.e., m retrieval images and m radii) are simultaneously submitted by users, then a cost-based dynamic retrieval (CDRS) scheduling procedure is invoked to efficiently and effectively identify the correlation among the retrieval spheres (requests) based on a cost model. Next, an index-based image set reduction (ISR) is performed at the execution-node level in parallel. Then, a refinement processing of the candidate images is conducted to get the answers. Finally, at the transmission-node level, the corresponding image fragment (IF) replicas are chosen based on an adaptive multi-resolution (AMR)-based IF replicas selection scheme, and transmitted to the user-node level by a priority-based IF replicas transmission (PIFT) scheme. The experimental results validate the efficiency and effectiveness of the algorithm in minimizing the response time and increasing the parallelism of I/O and CPU.