Mr. Jong In Kwak Profile

Jong In Kwak

MSEE at Kyungpook National Univ

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Proceedings Article | 23 May 2003 Paper

3D segmentation of breast tumor in ultrasound images

Jong In Kwak, Mal Nam Jung, Sang Hyun Kim, Nam Chul Kim

Proceedings Volume 5035, (2003) https://doi.org/10.1117/12.479903

KEYWORDS: Image segmentation, Tumors, Ultrasonography, 3D image processing, Breast, Distortion, Diagnostics, Imaging systems, Ultrasonics, 3D modeling

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This paper proposes a three-dimensional (3D) region-based segmentation algorithm for extracting a diagnostic tumor from ultrasound images by using a split-and-merge and seeded region growing with a distortion-based homogeneity cost. In the proposed algorithm, 2D cutting planes are first obtained by the equiangular revolution of a cross sectional plane on a reference axis for a 3D volume data. In each cutting plane, an elliptic seed mask that is included tightly in a tumor of interest is set. At the same time, each plane is finely segmented using the split-and-merge with a distortion-based cost. In the result segmented finely, all of the regions that are across or contained in the elliptic seed mask are then merged. The merged region is taken as a seed region for the seeded region growing. In the seeded region growing, the seed region is recursively merged with adjacent regions until a predefined condition is reached. Then, the contour of the final seed region is extracted as a contour of the tumor. Finally, a 3D volume of the tumor is rendered from the set of tumor contours obtained for the entire cutting planes. Experimental results for a 3D artificial volume data show that the proposed method yields maximum three times reduction in error rate over the Krivanek’s method. For a real 3D ultrasonic volume data, the error rates of the proposed method are shown to be lower than 17% when the results obtained manually are used as a reference data. It also is found that the contours of the tumor extracted by the proposed algorithm coincide closely with those estimated by human vision.

Proceedings Article | 30 May 2001 Paper

Content-based ultrasound image retrieval using magnitude frequency spectrum

Jae Gon Son, Jong Kwak, Sang Kim, Nam Chul Kim

Proceedings Volume 4325, (2001) https://doi.org/10.1117/12.428219

KEYWORDS: Image retrieval, Ultrasonography, Feature extraction, Databases, Wavelets, Speckle, Visualization, Medical imaging, Signal to noise ratio, Imaging systems

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We propose an efficient method for content-based ultrasound image retrieval using magnitude frequency spectrum and implement an ultrasound image retrieval system based on the proposed method. The target images are ultrasound images of adult organs. A trained staff often acquires such images so that images of the same kind of organs are very similar, although their locations may not exactly coincide. Therefore, the magnitude frequency spectrum, which has a translation-invariant property, is used as a feature for content-based retrieval. A test image database is composed of real ultrasound images. As a retrieval result, a specified number of highly similar target images are retrieved from all the target images. If all the target images in the database are pre-classified into organs of the same kind, the retrieved images are selected among the images whose class is the same as that of the highest similarity image. Experimental results of the proposed method is superior to other methods. The proposed method especially yields further performance improvement by using the pre-classification. Moreover, it is found from the experimental results that the magnitude frequency spectrum method is robust to the speckle noise that usually exists in ultrasound images.

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