Abstract

Lesion segmentation is a vital step in a melanoma recognition system. Many algorithms were developed for the efficient skin lesion segmentation. Most of them fails to realize a perfect segmentation. This paper proposes a novel, fully automatic system, for the lesion segmentation in dermatograms. The proposed approach executes in two steps. Selection of root seed is the first step. All the lesion pixels in the dermatogram are identified during the second step. Traversal through a predefined lesion pixel path ensures the reachability of all lesion pixels irrespective of the possible lesion discontinuity. The proposed algorithm is tested with two publically available dataset, PH2 and images of ISBI2016 challenge. Out of the six evaluation parameters, the proposed method shows the best values for specificity, accuracy, Hammuode distance and XOR. This confirms the merit of the proposal with respect to existing popular methods.

中文翻译：

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自动皮肤病变分割—通过像素路径填充病变的新方法

摘要

病变分割是黑色素瘤识别系统中至关重要的一步。为有效的皮肤病变分割开发了许多算法。他们中的大多数人都无法实现完美的细分。本文提出了一种新颖的全自动系统，用于皮肤病图中的病变分割。所提出的方法分两个步骤执行。根种子的选择是第一步。在第二步中确定皮肤图中的所有病变像素。遍历预定义的病变像素路径可确保所有病变像素的可及性，而不考虑可能的病变不连续性。该算法通过两个公开可用的数据集PH2和ISBI2016挑战图像进行了测试。在六个评估参数中，所提出的方法显示出最佳的特异性，准确性，Hammuode距离和XOR值。