Rib shape recognition in lung x-ray images for intelligent assistance

Hideyuki Sakaida; Akira Oosawa; Kazuo Shimura

doi:10.1117/12.652110

16 March 2006 Rib shape recognition in lung x-ray images for intelligent assistance

Hideyuki Sakaida, Akira Oosawa, Kazuo Shimura

Proceedings Volume 6145, Medical Imaging 2006: PACS and Imaging Informatics; 61451H (2006) https://doi.org/10.1117/12.652110
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

The purpose of this research is to develop a method for recognizing shapes of ribs in chest x-rays, which can be utilized as intelligent assistance to diagnosis to decrease false positives (FPs) due to ribs in chest CAD and automatically generate a schema in report. Shapes of ribs are manually extracted from several CR images to create a rib shape model using PDM, in which shapes of anterior/posterior ribs are represented as sets of coordinates and an arbitrary shape of a rib is expressed only with principle components that have a high contribution ratio to shape variation. Shapes of ribs in a chest X-ray image are identified as follows: (a) Identify the lung field. (b) Find an allowable range of weights of principle components in the shape model within which the model aligns to an edge of the lung field (a). (c) Create several shape model images by applying different weights of principle components. (d) Apply a six-direction Gabor filter to the X-ray image and each one of the shape model images to create an image containing only rib elements. (e) From images created in (d), search for a shape model image that shows the highest correlation coefficient with the X-ray image.We applied the rib shape model to 100 test images while changing weights of principle components. We were able to identify positions of ribs and anatomical rib numbers with an average margin of error being no more than two fifths of a rib and a half of a rib in case of anterior ribs.

Citation Download Citation

Hideyuki Sakaida, Akira Oosawa, and Kazuo Shimura "Rib shape recognition in lung x-ray images for intelligent assistance", Proc. SPIE 6145, Medical Imaging 2006: PACS and Imaging Informatics, 61451H (16 March 2006); https://doi.org/10.1117/12.652110

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