影像處理方法及影像處理系統

專利類型

發明

專利國別 (專利申請國家)

中華民國

專利申請案號

102133053

專利證號

I 514328

專利獲證名稱

影像處理方法及影像處理系統

專利所屬機關 (申請機關)

國立臺灣大學

獲證日期

2015/12/21

技術說明

於本發明中，我們考慮一特殊結構，由彼此互動表面群與任意形狀區域組成。其中，任意形狀表示為目標區域本身並未含有特定指定的形狀。將此相互關係納入考慮對於具有微弱邊界、低對比和附著於周圍組織之數量眾多且複雜的目標物群之影像分析中具有提升邊緣輪廓擷取之準確程度。主要概念為結合圖形劃分(graph cut)(Boykov et al., 2006)和區域合併基於統計方法(Statistical region merging, SRM) (Nock et al., 2004)兩種演算法之優點。對於任意形狀的區域，利用圖形劃分(graph cut) (Boykov et al., 2006)具有形狀靈活性，建構相對應的結構子圖。而透過區域合併基於統計方法建立區域階層式之結構子圖，此法可建構出肺腫瘤之三維空間分佈形態。 Image segmentation for the demarcation of pulmonary nodules in CT images is intrinsically an arduous task. In this patent, an image segmentation framework is proposed by unifying the techniques of statistical region merging and conditional random field (CRF) with graph cut optimization to address the difficult problem of GGO nodules quantification in CT images. Different from traditional segmentation methods that use pixel-based approach such as region growing and morphological constraints, we employ a hierarchical segmentation tree to alleviate the effect of inhomogeneous attenuation. In addition to building perceptual prominent regions, we perform inference in CRF model based on restricting the pool of segmented regions. Following that, an inference CRF model is carried out to detect and localize individual object instances in CT images.

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