Enhancing regional lymph nodes from endoscopic ultrasound images

Ifeoma Nwogu; Vipin Chaudhary

doi:10.1117/12.770642

26 March 2008 Enhancing regional lymph nodes from endoscopic ultrasound images

Ifeoma Nwogu, Vipin Chaudhary

Proceedings Volume 6914, Medical Imaging 2008: Image Processing; 691425 (2008) https://doi.org/10.1117/12.770642
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Esophageal ultrasound (EUS) is particularly useful for isolating lymph nodes in the N-staging of esophageal cancer, a disease with very poor overall prognosis. Although EUS is relatively low-cost and real time, and it provides valuable information to the clinician, its usefulness to less trained "users" including opportunities for computer-aided diagnosis is still limited due to the strong presence of spatially correlated interference noise called speckles. To this end, in this paper, we present a technique for enhancing lymph nodes in EUS images by first reducing the spatial correlation of the specular noise and then using a modified structured tensor-based anisotropic filter to complete the speckle reduction process. We report on a measure of the enhancement and also on the extent of automatic processing possible, after the speckle reduction process has taken place. Also, we show the limitations of the enhancement process by extracting relevant lymph node features from the despeckled images. When tested on five representative classes of esophageal lymph nodes, we found the despeckling process to greatly reduce the specularity of the original EUS images, therefore proving very useful for visualization purposes. But it still requires additional work for the complete automation of the lymph node characterizing process.

Citation Download Citation

Ifeoma Nwogu and Vipin Chaudhary "Enhancing regional lymph nodes from endoscopic ultrasound images", Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 691425 (26 March 2008); https://doi.org/10.1117/12.770642

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KEYWORDS

Lymphatic system

Anisotropic filtering

Image filtering

Digital filtering

Nonlinear filtering

Image processing

Image segmentation

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