Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches

Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches

Biomedical imaging Is an important source of information in cancer research. Characterizations of cancer morphology at onset, progression, and in response to treatment provide complementary information to that gleaned from genomics and clinical data. Accurate extraction and classification of both vi...

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Bibliographic Details
Main Authors: Tahsin Kurc, Spyridon Bakas, Xuhua Ren, Aditya Bagari, Alexandre Momeni, Yue Huang, Lichi Zhang, Ashish Kumar, Marc Thibault, Qi Qi, Qian Wang, Avinash Kori, Olivier Gevaert, Yunlong Zhang, Dinggang Shen, Mahendra Khened, Xinghao Ding, Ganapathy Krishnamurthi, Jayashree Kalpathy-Cramer, James Davis, Tianhao Zhao, Rajarsi Gupta, Joel Saltz, Keyvan Farahani
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-02-01
Series:Frontiers in Neuroscience
Subjects:
digital pathology
radiology
segmentation
classification
image analysis
deep learning
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2020.00027/full

Internet

https://www.frontiersin.org/article/10.3389/fnins.2020.00027/full

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