EM Senan, FW Alsaade… - Journal of Applied …, 2021 - jase.tku.edu.tw
… Mitosis detection in breastcancerhistologyimages with deep neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lec…
… diagnosis of breastcancer is extremely important. In the biomedical field, the examination and diagnosis of the breastcancerhistopathologicalimages by … The diagnosis process can be …
J Xie, R Liu, J Luttrell IV, C Zhang - Frontiers in genetics, 2019 - frontiersin.org
… deep learning and the challenges in histopathologicalimage analysis of breastcancer, this paper analyzes histopathologicalimages of breastcancer using deep learning techniques. …
… on mitosis detection in breastcancerhistopathologyimages. … on mitosis detection in breast cancerhistopathologyimages. … of mitosis detection in breastcancerhistopathologyimages. …
R Krithiga, P Geetha - Archives of Computational Methods in Engineering, 2021 - Springer
… It explores the image processing … aided diagnosis of cancer from H&E stained histopathology images. Figures 1 and 2 shows the various methods and modality of breastcancerimages. …
… suffers from breastcancer or not. We make use of publicly available BreastHistopathology Images … In this dataset, images are delineated to extract the exact regions of IDC. This dataset …
… The boundaries and edges of cells in breastcancerhistopathologypictures are critical for … maintains the edges of cells in psychological pictures of breastcancer, which is very important. …
… of the learned representations for breastcancerdiagnosis. … We used 240 digital breast histopathologyimages that were … associated with the BreastCancer Surveillance Consortium by …
AD Belsare, MM Mushrif, MA Pangarkar… - Tencon 2015-2015 …, 2015 - ieeexplore.ieee.org
… N×N is initial grid size of super pixel and σ is standard deviation of peak and is experimentally set as 10 for breasthistologyimages. For texture mapping of the breasthistologyimages …