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A data driven approach to cervigram image analysis and classification
Edward Kim,
Xiaolei Huang
College of Information Sciences and Technology
Huck Institutes of the Life Sciences
Research output
:
Chapter in Book/Report/Conference proceeding
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Chapter
43
Scopus citations
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Dive into the research topics of 'A data driven approach to cervigram image analysis and classification'. Together they form a unique fingerprint.
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Keyphrases
Image Classification
100%
Data-driven Approach
100%
Image Analysis
100%
Cervigram
100%
Region of Interest
40%
Cervical Cancer
40%
Cervix
40%
Texture Features
40%
Color Features
40%
Visual Inspection
20%
Binary Classification
20%
Acetic Acid
20%
Developing Countries
20%
Screening Method
20%
Treatment Options
20%
Leading Causes of Death
20%
Feature Extracting
20%
DNA Testing
20%
Classification Results
20%
HPV Infection
20%
Resource Scarcity
20%
Lifetime Risk
20%
Comparable Accuracy
20%
Disease Score
20%
Early Detection of Cervical Cancer
20%
Regular Screening
20%
Disease Classification
20%
Computer Science
Driven Approach
100%
Image Analysis
100%
Image Classification
100%
Texture Feature
100%
color feature
100%
Visual Inspection
50%
classification result
50%
Early Detection
50%
Binary Classification
50%
Mathematics
Binary Classification
100%