AUTOMATIC IDENTIFICATION AND DELINEATION OF GERM LAYER COMPONENTS IN H&E STAINED IMAGES OF TERATOMAS DERIVED FROM HUMAN AND NONHUMAN PRIMATE EMBRYONIC STEM CELLS.
AUTOMATIC IDENTIFICATION AND DELINEATION OF GERM LAYER COMPONENTS IN H&E STAINED IMAGES OF TERATOMAS DERIVED FROM HUMAN AND NONHUMAN PRIMATE EMBRYONIC STEM CELLS.
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DOI：
10.1109/isbi.2010.5490168
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发表时间：
2010-04-14
期刊：
影响因子：
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通讯作者：
Kovačević J
中科院分区：
文献类型：
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作者：
Bhagavatula R;Fickus M;Kelly W;Guo C;Ozolek JA;Castro CA;Kovačević J
我们提出了一种方法，用于自动识别和描绘的H&E染色的畸胎瘤来自人类和非人灵长类动物胚胎干细胞的图像中的胚层组件。这些细胞的生物学知识和理解可能会导致组织再生和修复，遗传和发育综合征的治疗，以及药物测试和发现的进步。由于畸胎瘤是来自三个初级胚胎胚层的组织的混乱组织，H&E畸胎瘤图像通常呈现多个组织，每个组织相对于每个单独的组织以及相对于其他组织具有复杂和不可预测的位置、形状和外观。虽然这些组织的视觉识别是耗时的，但它令人惊讶地准确，表明存在足够的视觉线索来完成任务。我们建议自动识别和描绘这些组织模仿这些视觉线索。我们使用基于像素的分类，导致在一个令人鼓舞的范围从74.9%到93.2%的分类精度为2至5个组织分类实验在不同的尺度。
We present a methodology for the automatic identification and delineation of germ-layer components in H&E stained images of teratomas derived from human and nonhuman primate embryonic stem cells. A knowledge and understanding of the biology of these cells may lead to advances in tissue regeneration and repair, the treatment of genetic and developmental syndromes, and drug testing and discovery. As a teratoma is a chaotic organization of tissues derived from the three primary embryonic germ layers, H&E teratoma images often present multiple tissues, each of having complex and unpredictable positions, shapes, and appearance with respect to each individual tissue as well as with respect to other tissues. While visual identification of these tissues is time-consuming, it is surprisingly accurate, indicating that there exist enough visual cues to accomplish the task. We propose automatic identification and delineation of these tissues by mimicking these visual cues. We use pixel-based classification, resulting in an encouraging range of classification accuracies from 74.9% to 93.2% for 2- to 5-tissue classification experiments at different scales.