3D matting: A benchmark study on soft segmentation method for pulmonary nodules applied in computed tomography

INTRODUCTION: In this paper, a semiautomatic image segmentation method for the serialized body slices of the Visible Human Project (VHP) is proposed. METHOD: In our method, we first verified the effectiveness of the shared matting method for the VHP slices and utilized it to segment a single image. Then, to meet the need for the automatic segmentation of serialized slice images, a method based on the parallel refinement method and flood-fill method was designed. The ROI (region of interest) image of the next slice can be extracted by using the skeleton image of the ROI in the current slice. RESULT: Utilizing this strategy, the color slice images of the Visible Human body can be continuously and serially segmented. This method is not complex but is rapid and automatic with less manual participation. CONCLUSION: The experimental results show that the primary organs of the Visible Human body can be accurately extracted.

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3D matting: A benchmark study on soft segmentation method for pulmonary nodules applied in computed tomography

Cited by 2 publications

References 40 publications

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Multimodal Image Confidence: A Novel Method for Tumor and Organ Boundary Representation

A Segmentation Method of Serialized Human Body Slices based on Matting Strategy and Skeleton Extraction

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