Evolving a Medical Image Similarity Search

Sujit Pal • Back to Haystack 2018

The talk covers the evolution of an Image Similarity Search Proof of Concept built to identify similar medical images. It discusses various image vectorizing techniques that were considered in order to convert images into searchable entities, an evaluation strategy to rank these techniques, as well as various indexing strategies to allow searching for similar images at scale.

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Sujit Pal

Sujit Pal works at Elsevier Labs, an advanced technology group within Elsevier. He introduction to search was as part of a team at CNET Networks implementing ATOMICS, a MySQL backed custom query engine to replace their legacy Altavista search engine. He was also one of the very early users of Solr within the company before it became an Apache project. He later joined Healthline, an ontology backed medical search company, where he helped make multiple improvements to the product, including moving it from Lucene to a Solr backed custom engine, and introducing various improvements that combined advances in Solr with Natural Language Processing and Machine Learning technologies. At Elsevier, he has worked on large-scale search quality measurement, and is currently looking at image understanding and search.