Theses and Dissertations from UMD

Permanent URI for this communityhttp://hdl.handle.net/1903/2

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM

More information is available at Theses and Dissertations at University of Maryland Libraries.

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Author: search.filters.author.Wang, FakaiSubject: search.filters.subject.attention model

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    JOINT SPACE NARROWING CLASSIFICATION BASED ON HAND X-RAY IMAGE
    (2020) Wang, Fakai; Wu, Min; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    X-ray images have been widely used by radiologists for disease diagnosis. For Rheumatoid Arthritis (RA), Joint Space Narrowing (JSN) is one major symptom that can be read from X-ray images. In this thesis, we investigate the JSN classification for RA diagnosis in terms of methodology, data analysis, neural network models, performance analysis. First, we perform the statistical analysis of X-ray data and design a baseline convolutional neural network (CNN). We show algorithms to extract joint patches. Then we conduct prediction analysis. Second, we design the fusion model to harness the correlation between the same type of joints. Sharing information within one X-ray image would increase the prediction performance. We also compare unified classifiers and separate classifiers. Third, we design the attention map model for joints with complex contexts, which filters out unrelated surroundings. We conclude that our models give good JSN prediction for Rheumatoid Arthritis.