Name
Title | ||
|---|---|---|
Analysis-synthesis model learning with shared features: A new framework for histopathological image classification |
Abstract | ||
|---|---|---|
Automated histopathological image analysis offers exciting opportunities for the early diagnosis of several medical conditions including cancer. There are however stiff practical challenges: 1.) discriminative features from such images for separating diseased vs. healthy classes are not readily apparent, and 2.) distinct classes, e.g. healthy vs. stages of disease continue to share several geometric features. We propose a novel Analysis-synthesis model Learning with Shared Features algorithm (ALSF) for classifying such images more effectively. In ALSF, a joint analysis and synthesis learning model is introduced to learn the classifier and the feature extractor at the same time. In this way, the computation load in patch-level based image classification can be much reduced. Crucially, we integrate into this framework the learning of a low rank shared dictionary and a shared analysis operator, which more accurately represents both similarities and differences in histopathological images from distinct classes. ALSF is evaluated on two challenging databases: (1) kidney tissue images provided by the Animal Diagnosis Lab (ADL) at the Pennsylvania State University and (2) brain tumor images from The Cancer Genome Atlas (TCGA) database. Experimental results confirm that ALSF can offer benefits over state of the art alternatives. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ISBI.2018.8363555 | 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) |
Keywords | Field | DocType |
low rank shared dictionary,shared analysis operator,histopathological images,ALSF,Animal Diagnosis Lab,Cancer Genome Atlas database,histopathological image classification,automated histopathological image analysis,early diagnosis,medical conditions including cancer,stiff practical challenges,discriminative features,healthy classes,geometric features,novel Analysis-synthesis model Learning,Shared Features algorithm,joint analysis,synthesis learning model,feature extractor,patch-level based image classification,brain tumor images,kidney tissue images | Pattern recognition,Computer science,Artificial intelligence,Extractor,Classifier (linguistics),Contextual image classification,Discriminative model,Model learning | Conference |
ISSN | ISBN | Citations |
1945-7928 | 978-1-5386-3637-4 | 0 |
PageRank | References | Authors |
0.34 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuelu Li | 1 | 10 | 4.24 |
| Vishal Monga | 2 | 679 | 57.73 |
| Arvind U. K. Rao | 3 | 10 | 0.87 |