視網膜影像自動排序及無縫拼接之演算法研究

A study of Algorithms for Automatic Retinal Image Prioritization, Stitching, and Blending

陳繹文(Yi-Wen Chen)

指導教授 ： 劉偉名

國立中正大學/工學院/資訊工程學系/碩士(2014年)

摘要

人類的視網膜對於視覺感知來說扮演著相當重要的角色。視網膜損傷所導致的視力喪失幾乎都是不可逆的。任何與視網膜相關的病變，都有可能導致失明。目前臨床上最方便被用來檢查視網膜的儀器為手持式眼底鏡。手持式眼底鏡有價格便宜，且便於攜帶等優點。但它的可視角度受到瞳孔限制，如同透過門縫來觀察房間內部，眼科醫師很難進行全面性的視網膜檢查。由於科技進步，數位手持式眼底鏡的問世使得視網膜影像可以電腦檔案型式被輸出，因此我們提出了全自動的視網膜影像全景拼貼系統，能夠將這些可視角度較小的影像拼貼成較大的影像，搭配上述新型眼底鏡可於診間外協助醫生進行快速且全面性的眼底疾病篩檢。
我們的方法包括了對輸入的一系列影像進行挑選、決定視網膜影像合併的優先順序、影像拼接以及降低因為拼接過程中所造的鬼影以及明顯色差，這些步驟都是專門為視網膜影像所設計。實驗結果顯示，我們所提出的一系列演算法整合能夠有效的將影像拼接為一張品質良好的視網膜全景影像。

關鍵字

影像混合 ； 影像拼接 ； 視網膜影像處理 ； 影像排序

並列摘要

The retina of human plays an important role in visual perception. Vision loss caused by retinal damage is almost irreversible and permanent. Any retinopathy could eventually lead to blindness. Current the handheld ophthalmoscope is the most convenient tool used in common clinical fundus examination due to its portability and cheap price. However, its viewing angle is too limited by the pupil to be used for a comprehensive ophthalmology examination, which is like exploring a room through a crack between the door and wall. With the technology improvement, the retinal images can be outputted from a digital handheld ophthalmoscope. Therefore we propose an automatic retinal image stitching approach to generate a larger field of view (FOV) via stitching a series of images of the same retina with different but partially overlapped FOV.
The approach includes input selection, stitching order prioritization, image stitching, and removal of stitching artifacts such as ghost shadow and color difference (blending). These procedures are all designed for retinal images. Our experiments have demonstrated that the integration allows us to create high quality retinal panorama.

並列關鍵字

Image blending ； Image stitching ； Retinal image processing ； Image prioritization

參考文獻

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