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Titlebook: Computational Pathology and Ophthalmic Medical Image Analysis; First International Danail Stoyanov,Zeike Taylor,Hrvoje Bogunovic Conferenc

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書(shū)目名稱(chēng)Computational Pathology and Ophthalmic Medical Image Analysis
副標(biāo)題First International
編輯Danail Stoyanov,Zeike Taylor,Hrvoje Bogunovic
視頻videohttp://file.papertrans.cn/233/232887/232887.mp4
叢書(shū)名稱(chēng)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Computational Pathology and Ophthalmic Medical Image Analysis; First International  Danail Stoyanov,Zeike Taylor,Hrvoje Bogunovic Conferenc
描述.This book constitutes the refereed joint proceedings of the First International Workshop on Computational Pathology, COMPAY 2018, and the 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018...The 19 full papers (out of 25 submissions) presented at COMPAY 2018 and the 21 full papers (out of 31 submissions) presented at OMIA 2018 were carefully reviewed and selected. The COMPAY papers focus on artificial intelligence and deep learning. The OMIA papers cover various topics in the field of ophthalmic image analysis..
出版日期Conference proceedings 2018
關(guān)鍵詞Artificial intelligence; Classification; Computational pathology; Computer vision; Deep learning; Digital
版次1
doihttps://doi.org/10.1007/978-3-030-00949-6
isbn_softcover978-3-030-00948-9
isbn_ebook978-3-030-00949-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2018
The information of publication is updating

書(shū)目名稱(chēng)Computational Pathology and Ophthalmic Medical Image Analysis影響因子(影響力)




書(shū)目名稱(chēng)Computational Pathology and Ophthalmic Medical Image Analysis影響因子(影響力)學(xué)科排名




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書(shū)目名稱(chēng)Computational Pathology and Ophthalmic Medical Image Analysis被引頻次




書(shū)目名稱(chēng)Computational Pathology and Ophthalmic Medical Image Analysis被引頻次學(xué)科排名




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Construction of a Generative Model of?H&E Stained Pathology Images of?Pancreas Tumors Conditioned by is a genetically engineered mouse model of pancreas tumor. The model represents the correlation between the value at each voxel in the MRI image of the tumor and the pathology image patches that are observed at each portion corresponds to the location of the voxel in the MRI image. The model is rep
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Role of Task Complexity and Training in Crowdsourced Image Annotationing holds promise to address this demand, but so far feasibility has only be shown for simple tasks and not for high-quality annotation of complex structures which is often limited by shortage of experts. Third-year medical students participated in solving two complex tasks, labeling of images and d
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Capturing Global Spatial Context for Accurate Cell Classification in Skin Cancer Histology cancer, calls for a better understanding of the cancer-immune interface. Computational pathology provides a unique opportunity to spatially dissect such interface on digitised pathological slides. Accurate cellular classification is a key to ensure meaningful results, but is often challenging even
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Evaluating Out-of-the-Box Methods for the Classification of Hematopoietic Cells in Images of Stainedsification: not only are the cells more densely distributed, there are also significantly more types of hematopoietic cells. So far, several attempts have been made using custom image features and prior knowledge in form of cytoplasm and nuclei segmentations or a restricted number of cell types in p
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