Marking Time : increased scope and accuracy for sketch classification of the clock drawing test
Name
930617504-MIT.pdf
Description
Full printable version
Size
1.75 MB
Format
Adobe PDF
Checksum (MD5)
03e0b374738af5b172b15820f3dfb59b
Author(s)
Chien, Jonathan
Advisor(s)
Randall Davis.
Alternative Title
Increased scope and accuracy for sketch classification of the clock drawing test
Date Issued
2015
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis, I designed and implemented improvements to an automatic classifier for the digitized clock drawing test, a diagnostic tool for assessing cognitive impairment, which asks the patient to draw an analog clock face using a digital pen. The classifier handles both the grouping of strokes into clock components and the subsequent labeling of those groups. Despite the domain-specificity, classification is a challenging problem because the subject often has cognitive or motor impairments. It is thus important for the classifier to be able to handle a wide range of input with distorted, overwritten, or missing components. I improve the robustness of the classifier, particularly for messy clinical data, by incorporating intrinsic stroke properties, developing additional symbol recognizers, and creating a global context evaluator. I describe in this thesis properties for isolated symbol recognition, features for symbol recognition and match scoring, as well as common sense rules based on a symbol's local and global context in a drawing. I combine these elements into a new system that locally maximizes a global label assignment based on match quality and context. I demonstrate that this system accurately recognizes a wide variety of clinical input, improving overall classification performance.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 85-86).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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