Paper
23 February 2012 Automated incision line determination for virtual unfolded view generation of the stomach from 3D abdominal CT images
Tomoaki Suito, Masahiro Oda, Takayuki Kitasaka, Gen Iinuma M.D., Kazunari Misawa M.D., Shigeru Nawano M.D., Kensaku Mori
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Abstract
In this paper, we propose an automated incision line determination method for virtual unfolded view generation of the stomach from 3D abdominal CT images. The previous virtual unfolding methods of the stomach required a lot of manual operations such as determination of the incision line, which heavily tasks an operator. In general, an incision line along the greater curvature of the stomach is used for making pathological specimen. In our method, an incision line is automatically determined by projecting a centerline of the stomach onto the gastric surface from a projection line. The projection line is determined by using positions of the cardia and the pylorus, that can be easily specified by two mouse clicks. The process of our method is performed as follows. We extract the stomach region using a thresholding and a labeling processes. We apply a thinning process to the stomach region, and then we extract the longest line from the result of the thinning process. We obtain a centerline of the stomach region by smoothing the longest line by using a Bezier curve. The incision line is calculated by projecting the centerline onto the gastric surface from the projection line. We applied the proposed method to 19 cases of CT images. We automatically determined incision lines. Experimintal results showed our method was able to determine incision lines along the greater curvature for most of 19 cases.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tomoaki Suito, Masahiro Oda, Takayuki Kitasaka, Gen Iinuma M.D., Kazunari Misawa M.D., Shigeru Nawano M.D., and Kensaku Mori "Automated incision line determination for virtual unfolded view generation of the stomach from 3D abdominal CT images", Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 83151M (23 February 2012); https://doi.org/10.1117/12.911409
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KEYWORDS
Stomach

3D image processing

Computed tomography

Endoscopy

Cancer

Image processing

X-ray computed tomography

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