1. Quantitative analysis of high-resolution microendoscopic images for diagnosis of neoplasia in patients with Barrett’s esophagus 
Dongsuk Shin, PhD, Michelle H. Lee, MD, Alexandros D. Polydorides, MD, PhD, Mark C. Pierce, PhD, Peter M. Vila, MD, Neil D. Parikh, MD, Daniel G. Rosen, MD, Sharmila Anandasabapathy, MD, Rebecca R. Richards-Kortum, PhD 
Gastrointestinal Endoscopy 
Volume 83, Issue 1, Pages (January 2016)
DOI: /j.gie
Copyright © 2016 The Authors Terms and Conditions

2. Figure 1
Image analysis procedure: A, A circular region of interest is selected. B, Fiber pattern is associated with the structure of a fiber bundle. C, Fiber bundle is removed by using Gaussian filtering. D, The contrast of an image is enhanced by using adaptive histogram equalization. E, Nuclei are segmented. The size distribution of glandular features is determined by using granulometry. F, Quantitative image features are calculated. ROI, region of interest.
Gastrointestinal Endoscopy  , DOI: ( /j.gie )
Copyright © 2016 The Authors Terms and Conditions

3. Figure 2
Flowchart for visual classification. Scale bars represent 100 μm. LGD, low-grade dysplasia.
Gastrointestinal Endoscopy  , DOI: ( /j.gie )
Copyright © 2016 The Authors Terms and Conditions

4. Figure 3
Resulting classification trees. A, The training set. B, The validation set. A bar graph on top indicates the total number of images in the data set. Bar graphs on the bottom indicate the number of images classified as one of the categories. N/C, nuclear to cytoplasmic; LGD, low-grade dysplasia.
Gastrointestinal Endoscopy  , DOI: ( /j.gie )
Copyright © 2016 The Authors Terms and Conditions