• 제목/요약/키워드: Automatic anatomically adaptive image enhancement

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Automatic Anatomically Adaptive Image Enhancement in Digital Chest Radiography

  • Kim, Sung-Hyun;Lee, Hyoung-Koo;Ho, Dong-Su;Kim, Do-Il;Choe, Bo-Young;Suh, Tae-Suk
    • 한국의학물리학회:학술대회논문집
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    • 한국의학물리학회 2002년도 Proceedings
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    • pp.442-445
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    • 2002
  • We present an algorithm for automatic anatomically adaptive image enhancement of digital chest radiographs. Chest images were exposed using digital radiography system with a 0.143 mm pixel pitch, l4-bit gray levels, and 3121 ${\times}$ 3121 matrix size. A chest radiograph was automatically divided into two classes (lung field and mediastinum) by using a maximum likelihood method. Each pixel in an image was processed using fuzzy domain transformation and enhancement of both the dynamic range and local gray level variations. The lung fields were enhanced appropriately to visualize effectively vascular tissue, the bronchus, and lung tissue, etc as well as pneumothorax and other lung diseases at the same time with the desired mediastinum enhancement. A prototype implementation of the algorithm is undergoing trials in the clinical routine of radiology department of major Korean hospital.

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