Titlebook: Digital Pathology; 15th European Congre Constantino Carlos Reyes-Aldasoro,Andrew Janowczyk Conference proceedings 2019 Springer Nature Swit

迅速

書目名稱Digital Pathology影響因子(影響力)




書目名稱Digital Pathology影響因子(影響力)學科排名




書目名稱Digital Pathology網絡公開度




書目名稱Digital Pathology網絡公開度學科排名




書目名稱Digital Pathology被引頻次




書目名稱Digital Pathology被引頻次學科排名




書目名稱Digital Pathology年度引用




書目名稱Digital Pathology年度引用學科排名




書目名稱Digital Pathology讀者反饋




書目名稱Digital Pathology讀者反饋學科排名

climax

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/d/image/279586.jpg

Colonnade

Arboreal

Nancy Cushing,Michael Kilmister,Nathan Scottnstruct a large pan-cancer dataset for nuclei instance segmentation and classification, with minimal sampling bias. The dataset consists of 455 visual fields, of which 312 are randomly sampled from more than 20K whole slide images at different magnifications, from multiple data sources. In total the

Accrue

committed

“Ruins True Refuge”: Beckett and Pintercomputational resources has been achieved, there are still problems in WSI that need to be solved. A major challenge is the scan size. The dimensions of digitized tissue samples may exceed 100,000 by 100,000 pixels causing memory and efficiency obstacles for real-time processing. The main contributi

committed

“Ruins True Refuge”: Beckett and Pintercial tasks in image analysis. We propose a methodology to improve segmentability of histological images by making use of image-to-image translation. We generate virtual stains and exploit the additional information during segmentation. Specifically a very basic pixel-based segmentation approach is a

heart-murmur

Lymphocyte

饑荒