首页> 外文OA文献 >Figure 3: Schematic representation of the immune cell detection map (green dots) on a whole slide image, which is generated by overlaying original digital slide image with a posterior likelihood map (heatmap with blue background).

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Figure 3: Schematic representation of the immune cell detection map (green dots) on a whole slide image, which is generated by overlaying original digital slide image with a posterior likelihood map (heatmap with blue background).

机译：图3：通过将原始数字幻灯片图像覆盖与后部似然图（Heatmap与蓝色背景）来产生的整个幻灯片图像上的免疫细胞检测图（绿色点）的示意图。

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1. Quantification of prognostic immune cell markers in colorectal cancer using whole slide imaging tumor maps [J] . HalamaN., ZoernigI., SpilleA., Analytical and quantitative cytology and histology . 2010,第6期

机译：使用全玻片成像肿瘤图量化大肠癌预后免疫细胞标志物
2. Comparing whole slide digital images versus traditional glass slides in the detection of common microscopic features seen in dermatitis [J] . Nikki S Vyas, Michael Markow, Carlos Prieto-Granada, Journal of Pathology Informatics . 2016,第1期

机译：在检测皮炎中常见的微观特征时，将整个载玻片数字图像与传统载玻片进行比较
3. Automated computational detection, quantitation, and mapping of mitosis in whole-slide images for clinically actionable surgical pathology decision support [J] . Munish Puri, Shelley B Hoover, Stephen M Hewitt, Journal of Pathology Informatics . 2019,第1期

机译：用于临床可行的外科病理学决策支持的全幻灯片中的自动计算检测，定量和丝分裂的映射
4. Can ImageNet feature maps be applied to small histopathological datasets for the classification of breast cancer metastatic tissue in whole slide images? [C] . T. Rai, A. Morisi, B. Bacci, SPIE Medical Imaging Conference . 2019

机译：Imagenet特征图可以应用于整个幻灯片图像中乳腺癌转移组织的分类的小组织病理学数据集吗？
5. John Wymer's DC: A Digital Integration Project for Image Collections Designing a Map Interface for Historic Image Overlay. [D] . Richardson, Jessica E. 2016

机译：约翰·怀默（John Wymer）的DC：用于图像收集的数字集成项目，设计用于历史图像叠加的地图界面。
6. SuperHistopath: A Deep Learning Pipeline for Mapping Tumor Heterogeneity on Low-Resolution Whole-Slide Digital Histopathology Images [O] . Konstantinos Zormpas-Petridis, Rosa Noguera, Daniela Kolarevic Ivankovic, 2020

机译：超脑病：用于在低分辨率全载性数字组织病理学图像上映射肿瘤异质性的深度学习管道
7. Figure 6: (A and B) Heatmaps of fixations across the three viewing modes (small images, larger images, moving window) and tasks (trustworthiness and dominance ratings); (C and D) difference maps showing where more fixations were made for trustworthiness ratings than for dominance ratings, and vice versa. [O] . -1

机译：图6：（a和b）三种观察模式（少量图像，较大的图像，移动窗口）和任务（可靠性和优势等级）的固定释放; （C和D）差异图显示为可靠性评级的更多固定，而不是用于优势评级，反之亦然。

Figure 3: Schematic representation of the immune cell detection map (green dots) on a whole slide image, which is generated by overlaying original digital slide image with a posterior likelihood map (heatmap with blue background).

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