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Methods for the evaluation of quality in machine processing of biomedical images

机译:生物医学图像机器加工质量评估方法

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The authors report on the main objectives and evaluation methods within microscopic image processing as related to the layer of smooth muscle of the intestinal wall. The presented images were acquired to facilitate effective study of diverticulosis. The general aim of image processing is to determine the number of cell nuclei highlighted by a contrast agent. By enabling comparison of the numbers of cell nuclei established in healthy individuals and in patients suffering from diverticulosis, the entire corpus of processing-related operations will contribute to further development within the recognition and assessment of structural changes in intestinal tissue layers. Image processing can be realized using traditional fast methods, for example thresholding with the subsequent summation of segments. The disadvantages of these methods consist in their inability to recognize overlapping nuclei, nuclei areas disrupted by image artefacts, or tissue microstructures; this deficiency causes a considerable error rate and necessitates manual postprocessing. However, such manual verification of results in a comprehensive image database is time-consuming and produces additional errors brought about by various aspects, for instance the verifying expert's fatigue. The metrics for the evaluation of quality in the obtained processing results consists in the values of correctly identified and incorrectly rejected.
机译:作者报告了显微图像处理中与肠壁平滑肌层有关的主要目标和评估方法。获取呈现的图像以促进憩室的有效研究。图像处理的总体目标是确定造影剂突出显示的细胞核数量。通过比较健康个体和患有憩室病的患者中建立的细胞核数目,整个与处理相关的操作将在识别和评估肠组织层结构变化的过程中进一步发展。可以使用传统的快速方法来实现图像处理,例如使用阈值和随后的分段总和。这些方法的缺点在于无法识别重叠的核,被图像伪像破坏的核区域或组织的微结构。这种缺陷会导致相当大的错误率,并且需要进行手动后处理。但是,在全面的图像数据库中对结果进行手动验证非常耗时,并且会产生由各个方面(例如,验证专家的疲劳)带来的其他错误。在获得的处理结果中评估质量的指标包括正确识别和错误拒绝的值。

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