E Stratmann | PubMed Health

PubMed2000

Graphically-enabled integration of bioinformatics tools allowing parallel execution.

Rapid analysis of large amounts of genomic data is of great biological as well as medical interest. This type of analysis will greatly benefit from the ability to rapidly assemble a set of related analysis programs and to exploit the power of parallel computing. TurboGenomics, which is a software package currently in its alpha-testing phase, allows integration of heterogeneous software components to be done graphically. In addition, the tool is capable of making the integrated components run in parallel. To demonstrate these abilities, we use the tool to develop a Web-based application that allows integrated access to a set of large-scale sequence data analysis programs used by a transposon-insertion based yeast genome project. We also contrast the differences in building such an application with and without using the TurboGenomics software.

Computational Biology↗

PubMedDate not supplied

PathMaster: content-based cell image retrieval using automated feature extraction.

OBJECTIVE: Currently, when cytopathology images are archived, they are typically stored with a limited text-based description of their content. Such a description inherently fails to quantify the properties of an image and refers to an extremely small fraction of its information content. This paper describes a method for automatically indexing images of individual cells and their associated diagnoses by computationally derived cell descriptors. This methodology may serve to better index data contained in digital image databases, thereby enabling cytologists and pathologists to cross-reference cells of unknown etiology or nature. DESIGN: The indexing method, implemented in a program called PathMaster, uses a series of computer-based feature extraction routines. Descriptors of individual cell characteristics generated by these routines are employed as indexes of cell morphology, texture, color, and spatial orientation. MEASUREMENTS: The indexing fidelity of the program was tested after populating its database with images of 152 lymphocytes/lymphoma cells captured from lymph node touch preparations stained with hematoxylin and eosin. Images of "unknown" lymphoid cells, previously unprocessed, were then submitted for feature extraction and diagnostic cross-referencing analysis. RESULTS: PathMaster listed the correct diagnosis as its first differential in 94 percent of recognition trials. In the remaining 6 percent of trials, PathMaster listed the correct diagnosis within the first three "differentials." CONCLUSION: PathMaster is a pilot cell image indexing program/search engine that creates an indexed reference of images. Use of such a reference may provide assistance in the diagnostic/prognostic process by furnishing a prioritized list of possible identifications for a cell of uncertain etiology.

Abstracting and Indexing↗