A method for the estimation of the hemoglobin distribution in gastroscopic images

The assessment of blood flow in the gastrointestinal mucosa could be a useful indicator for the diagnosis and treatment of several diseases, such as ulcers, gastritis, colitis or early cancer. The quantity of blood flow is roughly estimated by computing the spatial hemoglobin distribution in the muc...

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Bibliographic Details
Published in:International journal of bio-medical computing 1996-06, Vol.41 (3), p.153-165
Main Authors: Englmeier, K.-H., Herpers, R., Jacoby, R.S., Zwiebel, F.M.
Format: Article
Language:English
Subjects:
Algorithms
Blood flow
Colitis - diagnosis
Colonoscopy
Color
Color image analysis
Distribution of hemoglobin
Endoscopic true-color images
Gastric Mucosa - anatomy & histology
Gastric Mucosa - blood supply
Gastric Mucosa - metabolism
Gastritis - diagnosis
Gastroscopy
Hemoglobins - metabolism
Humans
Image Processing, Computer-Assisted
Intestinal Mucosa - anatomy & histology
Intestinal Mucosa - blood supply
Intestinal Mucosa - metabolism
Intestinal Neoplasms - diagnosis
Light
Reflectance spectrophotometry
Regional Blood Flow
Reproducibility of Results
Spectrophotometry
Stomach Neoplasms - diagnosis
Stomach Ulcer - diagnosis
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Summary:The assessment of blood flow in the gastrointestinal mucosa could be a useful indicator for the diagnosis and treatment of several diseases, such as ulcers, gastritis, colitis or early cancer. The quantity of blood flow is roughly estimated by computing the spatial hemoglobin distribution in the mucosa. The method presented here enables a practical realization by calculating approximately the hemoglobin concentration based on a spectrophotometric analysis of endoscopic true-color images, which are recorded during routine examinations. A system model based on the reflectance spectroscopic law of Kubelka-Munk is derived, which enables an estimation of the hemoglobin concentration by means of the color values of the images. Additionally, a transformation of the color values is developed, in order to improve the luminance independence. Applying this transformation and estimating the hemoglobin concentration for each pixel of interest, the hemoglobin distribution can be computed. The results obtained are mostly independent of luminance. An initial validation of the method is made by a quantitative estimation of the reproducibility.
ISSN:0020-7101
DOI:10.1016/0020-7101(96)01171-3