Using component technologies for web based wavelet enhanced mammographic image visualization

Citation
P. Sakellaropoulos et al., Using component technologies for web based wavelet enhanced mammographic image visualization, MED INF IN, 25(3), 2000, pp. 171-181
Citations number
21
Categorie Soggetti
Research/Laboratory Medicine & Medical Tecnology
Journal title
MEDICAL INFORMATICS AND THE INTERNET IN MEDICINE
ISSN journal
14639238 → ACNP
Volume
25
Issue
3
Year of publication
2000
Pages
171 - 181
Database
ISI
SICI code
1463-9238(200007/09)25:3<171:UCTFWB>2.0.ZU;2-C
Abstract
The poor contrast detectability of mammography can be dealt with by domain specific software visualization tools. Remote desktop client access and tim e performance limitations of a previously reported visualization tool are a ddressed, aiming at more efficient visualization of mammographic image reso urces existing in web or PACS image servers. This effort is also motivated by the fact that at present, web browsers do not support domain-specific me dical image visualization. To deal with desktop client access the tool was redesigned by exploring component technologies, enabling the integration of stand alone domain specific mammographic image functionality in a web brow sing environment (web adaptation). The integration method is based on Activ eX Document Server technology. ActiveX Document is a part of Object Linking and Embedding (OLE) extensible systems object technology, offering new ser vices in existing applications. The standard DICOM 3.0 part 10 compatible i mage-format specification Papyrus 3.0 is supported, in addition to standard digitization formats such as TIFF. The visualization functionality of the tool has been enhanced by including a fast wavelet transform implementation , which allows for real time wavelet based contrast enhancement and denoisi ng operations. Initial use of the tool with mammograms of various breast st ructures demonstrated its potential in improving visualization of diagnosti c mammographic features. Web adaptation and real time wavelet processing en hance the potential of the previously reported tool in remote diagnosis and education in mammography.