Automated tissue image analysis

Automated tissue imaging analysis can significantly reduce uncertainty in characterizing tumors compared to evaluations done by histologists,[1] or improve the prediction rate of recurrence of some cancers.

Coupled with advanced widefield microscopes and various algorithms for image restoration, this approach can provide better results than confocal techniques at comparable speeds and lower costs.

[5] The United States Food and Drug Administration classifies these systems as medical devices, under the general instrumentation category of automatic test equipment.

These potential and irreducible inconsistencies in analysis results motivated the development of Automated Tissue Image Systems.

Once the sample image has been acquired and resident in the computer's random access memory as a large array of 0's and 1's, a programmer knowledgeable in cellular architecture can develop deterministic algorithms applied to the entire memory space to detect cell patterns from previously defined cellular structures and formations known to be significant.