Topological image modification for object detection and topological image processing of skin lesions.

Topological image modification for object detection and topological image processing of skin lesions.
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DOI:
10.1038/s41598-020-77933-y
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发表时间:
2020-12-03
期刊:
影响因子:
4.6
通讯作者:
Gevaert O
Gevaert O
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Vandaele R;Nervo GA;Gevaert O

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我们提出一种基于拓扑数据分析(TDA)的新方法,该方法由拓扑图像修改(TIM)和拓扑图像处理(TIP)组成,用于目标检测。通过这种新引入的方法,我们人为地破坏不相关的目标,并在图像的不相关区域构建具有已知拓扑性质的新目标。这确保我们能够识别图像相关区域中的重要目标。我们通过持久同调做到这一点,它使我们能够同时选择合适的阈值以及与这些阈值相对应的目标,并将它们从图像的噪声背景中分离出来。这产生了一幅以完全无监督的方式处理的新图像,从该图像中可以更有效地提取重要目标。我们通过对ISIC 2018皮肤病变图像进行无监督分割的案例研究,证明了所提出的拓扑图像处理方法的有效性。该项目的代码可在https://bitbucket.org/ghentdatascience/topimgprocess获取。
We propose a new method based on Topological Data Analysis (TDA) consisting of Topological Image Modification (TIM) and Topological Image Processing (TIP) for object detection. Through this newly introduced method, we artificially destruct irrelevant objects, and construct new objects with known topological properties in irrelevant regions of an image. This ensures that we are able to identify the important objects in relevant regions of the image. We do this by means of persistent homology, which allows us to simultaneously select appropriate thresholds, as well as the objects corresponding to these thresholds, and separate them from the noisy background of an image. This leads to a new image, processed in a completely unsupervised manner, from which one may more efficiently extract important objects. We demonstrate the usefulness of this proposed method for topological image processing through a case-study of unsupervised segmentation of the ISIC 2018 skin lesion images. Code for this project is available on https://bitbucket.org/ghentdatascience/topimgprocess.
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