Bisque: A Scalable Biological Image Database and Analysis Framework - High-Throughput Image Reconstruction and Analysis - page 296

Figure 13.6 Bisque tagger prototype: Tags represent an expandable set of fields associated with
the image. Tags can be added, deleted, and modified. Graphical markup will also be available with
functions similar to the digital notebook.

needed. It should be noted that in this configuration, Bisque can be used to
develop and test data models before migrating to Bisque/OME servers and
fixed data models.
The core aggregate service allows users to locally tag and store local analysis
results while operating on remote (bridged) images and data. The aggregate
service combines the metadata from several sources including bridge servers.

Image similarity index: The similarity search server permits scalable index-
ing and search by content for biological images. The search server maintains
its own index and provides content-based search. The similarity index builds
on our core servers using the data server and the image server. The data
server defines basic image identifiers while the image server provides pixel
data. The framework defines the interface the similarity-servers must adhere
to, including initially building the index, extraction of relevant features, and
searching. The framework does not specify the implementation of the index-

￿