Name
Title | ||
|---|---|---|
Distinguishing patients with celiac disease by quantitative analysis of videocapsule endoscopy images |
Abstract | ||
|---|---|---|
Background: Although videocapsule endoscopy images are helpful in the evaluation of celiac disease, their interpretation is subjective. Quantitative disease markers could assist in determining the extent of villous atrophy and response to treatment. Method: Capsule endoscopy images were acquired from celiac patients with small bowel pathology (N=11) and from control patients (N=10). Image resolution was 576x576 pixels in dimension, 256 grayscale levels, and had a 2s^-^1 frame rate. Pixel brightness and image texture were measured over 10x10 pixel subimages and then averaged for 56x56 subimages per frame. Measurements were obtained at five locations from proximal to distal small intestine in each patient. At each location, measurements were calculated using 200 consecutive image frames (100s). Mean frame-to-frame pixel brightness, image texture, and periodicity in brightness, an estimate of wall motion or intestinal motility, were computed and used for classification with a nonlinear discriminant function. Results: From pooled data, celiac images had greater texture than did images from control patients (p |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.cmpb.2010.02.005 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
quantitative analysis | Computer vision,Image texture,Endoscopy,Artificial intelligence,Pixel,Atrophy,Capsule endoscopy,Image resolution,Medicine,Grayscale,Discriminant function analysis | Journal |
Volume | Issue | ISSN |
100 | 1 | 0169-2607 |
Citations | PageRank | References |
28 | 2.23 | 1 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Edward J. Ciaccio | 1 | 165 | 30.79 |
| Christina A. Tennyson | 2 | 36 | 3.13 |
| Suzanne K. Lewis | 3 | 42 | 5.43 |
| Suneeta Krishnareddy | 4 | 28 | 2.23 |
| Govind Bhagat | 5 | 41 | 5.46 |
| Peter H. R. Green | 6 | 48 | 5.26 |