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Recognition of lung nodule shadows from chest X‐ray CT images using 3D Markov random field models by Hotaka Takizawa; Shinji Yamamoto; Tohru Nakagawa; Tohru Matsumoto; Yukio Tateno; Takeshi Iinuma; Mitsuomi Matsumoto is a Computer Science article available to read on EtoBox.

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## Abstract This paper presents a scheme for recognizing nodule shadows that are candidate lung cancer lesions from chest X‐ray CT images. In recognizing shadow candidates, their surrounding shadows give useful information. The proposed scheme recognizes nodule shadows by formulating the relationships between shadow candidates and their surrounding shadows in the framework of a three‐dimensional Markov random field model. First, it detects isolated shadows that become nodule candidates, extracts a volume of interest that includes shadow candidates, and divides the volume of interest into rectangular regions. It expresses nodules and blood vessels in three‐dimensional geometric models of spheres and cylinders, and lists a number of object models having high probabilities of existing in each rectangular region. It then generates a combination of object models by assembling the physical models. It formulates the relationships between each rectangular region, anatomical verifications of the object model combinations and the degree of agreement between observed CT images and object model combinations in the framework of a three‐dimensional Markov random field model, and computes the pro

Who reads Recognition of lung nodule shadows from chest X‐ray CT images using 3D Markov random field models?

Author

Hotaka Takizawa; Shinji Yamamoto; Tohru Nakagawa; Tohru Matsumoto; Yukio Tateno; Takeshi Iinuma; Mitsuomi Matsumoto

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 0882-1666)

Published

2004

Language

EN

Field

Computer Science (Physical Sciences)