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Image-asssited system for the diagnosis of bladder tumor recurrence

机译:影像辅助系统诊断膀胱肿瘤复发

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This paper presents a system for detecting mor-phometric properties of bladder mucosa images obtained with a cystoscope. These properties are calculated for obtaining information about the probability of tumour recurrence. For this purpose, illumination problems of these images have been corrected to apply a vessels segmentation algorithm. Finally, the number of bifurcations of the vascular tree and a ratio Vessels/Bladder area are calculated to validate the hypothesis mentioned above. This validation is carried out with 20 images of bladder mucosa obtaining very promising results, in particular the presented algorithm achieves a sensibility of 0.8571 and a specificity of 1. Consequently, the system proposed in this paper shows valuable properties for the specific objective pointed, i.e, the characterization of the bladder tumour recurrence.
机译:本文提出了一种用于检测用膀胱镜获得的膀胱粘膜图像形态特征的系统。计算这些特性是为了获得有关肿瘤复发概率的信息。为此,已对这些图像的照明问题进行了纠正,以应用血管分割算法。最后,计算血管树的分叉数和血管/膀胱面积比以验证上述假设。用20幅膀胱粘膜图像进行了验证,获得了非常有希望的结果,特别是所提出的算法实现了0.8571的灵敏度和1的特异性。因此,本文提出的系统显示了针对特定目标的有价值的特性,即,表征膀胱肿瘤复发。

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