Improving Medical Experience With Lung Histopathological Image Classification for Smart Healthcare
Author:
Affiliation:
1. College of Information Engineering, Jiaozuo Normal College, Jiaozuo, China
2. First Affiliated Hospital, Henan Polytechnic University, Jiaozuo, Henan, China
3. Department of Computer Science and Technology, Nanjing University, Nanjing, China
Funder
Henan Province Soft Science Project
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/30/10510045/10457545.pdf?arnumber=10457545
Reference26 articles.
1. Lung cancer subtype classification using histopathological images based on weakly supervised multi-instance learning
2. Tumor-identification method for predicting recurrence of early-stage lung adenocarcinoma using digital pathology images by machine learning
3. Automatic Cell Detection in Bright-Field Microscope Images Using SIFT, Random Forests, and Hierarchical Clustering
4. ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network
5. Effective segmentation and classification for HCC biopsy images
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