A web-based solution for viewing large-sized microscopic images.
This paper demonstrates a pure web-based solution enabling the presentation of scanned pathologic microscopic images on the web. For each slide, an entire specimen is scanned, and a high-resolution digital image (in the order of giga-pixels) is reconstructed. These huge images are then tiled into many 256 x 256-pixel blocks with different resolutions, and information about the blocks of each scanned slide is included in an extensible markup language metafile. Based on the data, a virtual microscopy system is created for viewing the scanned pathologic slides on web. The functionalities (changing viewing resolution, location adjustment, and multimedia annotation presentation) of our virtual slide viewing system are accomplished using pure hypertext markup language (HTML) and JavaScript. We show that there is no need to add plug-in components to browsers in order to handle virtual slides on the web. In a heterogeneous healthcare environment, methods using pure HTML and JavaScript to deal with pathologic content are more appropriate than using proprietary technologies supported only by specific browsers.
Lien
Chung-Yueh
CY
Institute of Biomedical Engineering, National Yang Ming University, Taipei, Taiwan.
Teng
Hsu-Chih
HC
Chen
Deng-Ji
DJ
Chu
Woei-Chyn
WC
Hsiao
Chia-Hung
CH
D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D008853:Microscopy / Q000379:methods*; D011381:Programming Languages; D012984:Software; D046888:Tissue Array Analysis / Q000379:methods*; D014584:User-Computer Interface