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Integrated Radiology Image Search(IRIS)

Radiology teaching file search engine with ranked retrieval using ensemble of topic models

Priya Deshpande

DePaul University, ChicagoSeptember 9th, 2018

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Dr. Alexander Rasin

Dr. Eli BrownDr. Jacob FurstDr. Steven M. Montner Dr. Samuel G. Armato III Dr. Daniela Raicu

Priya Deshpande

Research Group

Matt Nykaza Cara Gilad Teresa Manuel

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Agenda

Introduction to Radiology Teaching File SystemsMotivationProject OverviewArchitecture ResultsConclusion and Future work

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Role of Teaching Files in RadiologyExample: MIRC: Medical Imaging Resource Community

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Radiology Teaching File Data Sources and Search Engines

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Motivation

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IRIS: Integrated Radiology Image Search

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Integrated Radiology Image Search Engine

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IRIS Ranked Retrieval with Ensemble of Topic Models

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Topic modelling to find alternate spelling and similar words

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IRIS – Rich Integrated teaching files repository with NLP Support Text results augmented with image-based results Topic modeling improves search results by re-ranking teaching

cases Tools like IRIS can enhance the productivity and effectiveness of

radiologists Future Work: Text based-search with hierarchical text structure and proximity of words Create patches – Analyse an Image patches Improve image-based results using deep learning algorithms

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Conclusions and Future Work

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Acknowledgements

MIRC and MyPacs teaching file repositories for making their datasetspublicly available. RadLex and SNOMED CT groups for making their ontologies freely

available for research purposes.

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Dr. Alexander RasinCara Gilad

Teresa Manuel Matt NykazaDr. Eli Brown

Dr. Jacob FurstDr. Steven M. MontnerDr. Samuel G. Armato III

Dr. Daniela Raicu

Thank You!Co-Authors