MAGIC-5: an Italian mammographic database of digitised images for research

Tangaro, S., Bellotti, R., De Carlo, F., Gargano, G., Lattanzio, E., Monno, P., Massafra, R., Delogu, P., Fantacci, M. E., Retico, A., and others. (2008) MAGIC-5: an Italian mammographic database of digitised images for research. La Radiologia Medica, 113 (4). pp. 477-485. ISSN 0033-8362. (doi:10.1007/s11547-008-0282-5) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:91795)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL: https://doi.org/10.1007/s11547-008-0282-5

Abstract

The implementation of a database of digitised mammograms is discussed. The digitised images were collected beginning in 1999 by a community of physicists in collaboration with radiologists in several Italian hospitals as a first step in developing and implementing a computer-aided detection (CAD) system. All 3,369 mammograms were collected from 967 patients and classified according to lesion type and morphology, breast tissue and pathology type. A dedicated graphical user interface was developed to visualise and process mammograms to support the medical diagnosis directly on a high-resolution screen. The database has been the starting point for developing other medical imaging applications, such as a breast CAD, currently being upgraded and optimised for use in a distributed environment with grid services, in the framework of the Instituto Nazionale di Fisicia Nucleare (INFN)-funded Medical Applications on a Grid Infrastructure Connection (MAGIC)-5 project.

Item Type:	Article
DOI/Identification number:	10.1007/s11547-008-0282-5
Uncontrolled keywords:	Databas; Mammography; Medical image processing; Grid
Subjects:	Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Institutional Unit:	Schools > School of Computing
Former Institutional Unit:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User:	Amy Boaler
Date Deposited:	30 Nov 2021 14:48 UTC
Last Modified:	22 Jul 2025 09:08 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/91795 (The current URI for this page, for reference purposes)

University of Kent Author Information

Masala, Giovanni Luca.

Creator's ORCID:	https://orcid.org/0000-0001-6734-9424
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