PathMaster: Content-based Cell Image Retrieval Using Automated Feature Extraction | Zendy

Mark E. Mattie | Zendy; Lawrence H. Staib | Zendy; Eric Stratmann | Zendy; Hemant D. Tagare | Zendy; John S. Duncan | Zendy; Perry L. Miller | Zendy

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PathMaster: Content-based Cell Image Retrieval Using Automated Feature Extraction

Author(s) -

Mark E. Mattie,

Lawrence H. Staib,

Eric Stratmann,

Hemant D. Tagare,

John S. Duncan,

Perry L. Miller

Publication year - 2000

Publication title -

journal of the american medical informatics association

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.614

H-Index - 150

eISSN - 1527-974X

pISSN - 1067-5027

DOI - 10.1136/jamia.2000.0070404

Subject(s) - computer science , search engine indexing , feature extraction , feature (linguistics) , database index , artificial intelligence , information retrieval , image retrieval , fidelity , medical diagnosis , automatic image annotation , pattern recognition (psychology) , image (mathematics) , pathology , medicine , telecommunications , philosophy , linguistics

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.

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