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A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
Published on: May 20, 2016
An Image Retrieval Pipeline in a Medical Data Integration Center
Ka Yung Cheng1, Santiago Pazmino1, Björn Bergh1
1Institute for Medical Informatics and Statistics, Kiel University and University Hospital Schleswig-Holstein, Kiel, Germany.
Abstract:
Medical images need annotations with high-level semantic descriptors, so that domain experts can search for the desired dataset among an enormous volume of visual media within a Medical Data Integration Center. This article introduces a processing pipeline for storing and annotating DICOM and PNG imaging data by applying Elasticsearch, S3 and Deep Learning technologies. The proposed method processes both DICOM and PNG images to generate annotations. These image annotations are indexed in Elasticsearch with the corresponding raw data paths, where they can be retrieved and analyzed.

