HISTOPATHOLOGY IMAGE REGISTRATION BY INTEGRATED TEXTURE AND SPATIAL PROXIMITY BASED LANDMARK SELECTION AND MODIFICATION.
HISTOPATHOLOGY IMAGE REGISTRATION BY INTEGRATED TEXTURE AND SPATIAL PROXIMITY BASED LANDMARK SELECTION AND MODIFICATION.
复制标题
通过基于集成纹理和空间邻近性的标志选择和修改进行组织病理学图像配准。
DOI：
10.1109/isbi48211.2021.9434114
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发表时间：
2021-04
期刊：
影响因子：
--
通讯作者：
Kong J
中科院分区：
文献类型：
--
作者：
Liu P;Wang F;Teodoro G;Kong J
三维 (3D) 数字病理学已经出现在下一代基于组织的癌症研究中。为了实现这种组织病理学图像体积分析，连续的组织病理学载玻片需要良好对齐。在本文中，我们提出了一种组织病理学图像配准微调方法，通过纹理和空间邻近度测量来集成地标评估。首先检测代表性解剖结构和图像角特征作为界标候选。接下来，我们通过利用图像纹理特征和地标空间邻近度度量来识别强匹配地标并修改弱匹配地标。大量实验的定性和定量结果表明，我们提出的方法是稳健的，可以进一步将我们之前配准图像集的配准精度分别提高 31.15%（相关性）、4.88%（互信息）和 41.02%（均方误差）。有希望的实验结果表明，我们的方法可以用作微调模块，以进一步提高配准精度，这是癌症研究的信息无损 3D 组织空间中组织学空间和形态学分析的前提。
Three-dimensional (3D) digital pathology has been emerging for next-generation tissue based cancer research. To enable such histopathology image volume analysis, serial histopathology slides need to be well aligned. In this paper, we propose a histopathology image registration fine tuning method with integrated landmark evaluations by texture and spatial proximity measures. Representative anatomical structures and image corner features are first detected as landmark candidates. Next, we identify strong and modify weak matched landmarks by leveraging image texture features and landmark spatial proximity measures. Both qualitative and quantitative results of extensive experiments demonstrate that our proposed method is robust and can further enhance registration accuracy of our previously registered image set by 31.15% (correlation), 4.88% (mutual information), and 41.02% (mean squared error), respectively. The promising experimental results suggest that our method can be used as a fine tuning module to further boost registration accuracy, a premise of histology spatial and morphology analysis in an information-lossless 3D tissue space for cancer research.
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影响因子：
10.9
作者：
Thirion, J P
通讯作者：
Thirion, J P
DOI：
10.1007/978-3-319-47118-1_8
发表时间：
2016-10
期刊：
Patch-based techniques in medical imaging : Second International Workshop, Patch-MI 2016, held in conjunction with MICCAI 2016, Athens, Greece, October 17, 2016 : proceedings. Patch-MI (Workshop) (2nd : 2016 : Athens, Greece)
影响因子：
--
作者：
Dalca AV;Bobu A;Rost NS;Golland P
通讯作者：
Golland P
影响因子：
10.6
作者：
Gigengack, Fabian;Ruthotto, Lars;Schaefers, Klaus P.
通讯作者：
Schaefers, Klaus P.
DOI：
10.1109/isbi.2017.7950552
发表时间：
2017-04
期刊：
Proceedings. IEEE International Symposium on Biomedical Imaging
影响因子：
--
作者：
Rossetti BJ;Wang F;Zhang P;Teodoro G;Brat DJ;Kong J
通讯作者：
Kong J
影响因子：
5.7
作者：
Vercauteren, Tom;Pennec, Xavier;Ayache, Nicholas
通讯作者：
Ayache, Nicholas