VSGD-Net: Virtual Staining Guided Melanocyte Detection on Histopathological Images.
VSGD-Net: Virtual Staining Guided Melanocyte Detection on Histopathological Images.
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DOI：
10.1109/wacv56688.2023.00196
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发表时间：
2023-01
期刊：
影响因子：
--
通讯作者：
Shapiro, Linda
中科院分区：
文献类型：
--
作者：
Liu, Kechun;Li, Beibin;Wu, Wenjun;May, Caitlin;Chang, Oliver;Knezevich, Stevan;Reisch, Lisa;Elmore, Joann;Shapiro, Linda
黑素细胞的检测是在皮肤活检标本上诊断黑色素瘤及其前体病变时评估黑素细胞生长模式的关键先决条件。然而，由于常规苏木精和曙红（H&E）染色图像中黑素细胞与其他细胞的视觉相似性，这种检测是具有挑战性的，导致当前细胞核检测方法的失败。诸如Sox 10的染色剂可以标记黑素细胞，但是它们需要额外的步骤和费用，因此在临床实践中不经常使用。为了解决这些限制，我们引入了VSGD-Net，这是一种新型的检测网络，通过从H&E到Sox 10的虚拟染色来学习黑素细胞识别。该方法在推理过程中只需要常规的H&E图像，从而为病理学家诊断黑色素瘤提供了一种有前途的方法。据我们所知，这是第一项研究，探讨了两个不同的病理染色之间使用图像合成功能的检测问题。大量的实验结果表明，我们提出的模型优于国家的最先进的黑素细胞检测核检测方法。源代码和预训练模型可在以下网址获得：https://github.com/kechunl/VSGD-Net
Detection of melanocytes serves as a critical prerequisite in assessing melanocytic growth patterns when diagnosing melanoma and its precursor lesions on skin biopsy specimens. However, this detection is challenging due to the visual similarity of melanocytes to other cells in routine Hematoxylin and Eosin (H&E) stained images, leading to the failure of current nuclei detection methods. Stains such as Sox10 can mark melanocytes, but they require an additional step and expense and thus are not regularly used in clinical practice. To address these limitations, we introduce VSGD-Net, a novel detection network that learns melanocyte identification through virtual staining from H&E to Sox10. The method takes only routine H&E images during inference, resulting in a promising approach to support pathologists in the diagnosis of melanoma. To the best of our knowledge, this is the first study that investigates the detection problem using image synthesis features between two distinct pathology stainings. Extensive experimental results show that our proposed model outperforms state-of-the-art nuclei detection methods for melanocyte detection. The source code and pre-trained model are available at: https://github.com/kechunl/VSGD-Net
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影响因子：
10.6
作者：
Mahmood F;Borders D;Chen RJ;Mckay GN;Salimian KJ;Baras A;Durr NJ
通讯作者：
Durr NJ
影响因子：
10.6
作者：
Liu, Shuting;Zhang, Baochang;He, Yonghong
通讯作者：
He, Yonghong
影响因子：
10.6
作者：
Knoll F;Holler M;Koesters T;Otazo R;Bredies K;Sodickson DK
通讯作者：
Sodickson DK
DOI：
10.1016/j.compmedimag.2018.08.010
发表时间：
2018-12-01
影响因子：
5.7
作者：
Hoefener, Henning;Homeyer, Andre;Hahn, Horst K.
通讯作者：
Hahn, Horst K.
影响因子：
3.9
作者：
Liu, Yiming;Zhang, Pengcheng;Gui, Zhiguo
通讯作者：
Gui, Zhiguo