Towards a repository for standardized medical image and signal case data annotated with ground truth

J Digit Imaging. 2012 Apr;25(2):213-26. doi: 10.1007/s10278-011-9428-4.

Abstract

Validation of medical signal and image processing systems requires quality-assured, representative and generally acknowledged databases accompanied by appropriate reference (ground truth) and clinical metadata, which are composed laboriously for each project and are not shared with the scientific community. In our vision, such data will be stored centrally in an open repository. We propose an architecture for a standardized case data and ground truth information repository supporting the evaluation and analysis of computer-aided diagnosis based on (a) the Reference Model for an Open Archival Information System (OAIS) provided by the NASA Consultative Committee for Space Data Systems (ISO 14721:2003), (b) the Dublin Core Metadata Initiative (DCMI) Element Set (ISO 15836:2009), (c) the Open Archive Initiative (OAI) Protocol for Metadata Harvesting, and (d) the Image Retrieval in Medical Applications (IRMA) framework. In our implementation, a portal bunches all of the functionalities that are needed for data submission and retrieval. The complete life cycle of the data (define, create, store, sustain, share, use, and improve) is managed. Sophisticated search tools make it easier to use the datasets, which may be merged from different providers. An integrated history record guarantees reproducibility. A standardized creation report is generated with a permanent digital object identifier. This creation report must be referenced by all of the data users. Peer-reviewed e-publishing of these reports will create a reputation for the data contributors and will form de-facto standards regarding image and signal datasets. Good practice guidelines for validation methodology complement the concept of the case repository. This procedure will increase the comparability of evaluation studies for medical signal and image processing methods and applications.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Database Management Systems / standards*
  • Databases, Factual / standards*
  • Diagnosis, Computer-Assisted / standards*
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Image Processing, Computer-Assisted / standards
  • Information Storage and Retrieval / methods*
  • Information Storage and Retrieval / standards
  • Quality Assurance, Health Care
  • Radiology Information Systems
  • Signal Processing, Computer-Assisted*
  • Software
  • Systems Integration
  • User-Computer Interface