Experiments in Molecular Subtype Recognition Based on Histopathology Images
| Authors | |
|---|---|
| Year of publication | 2016 |
| Type | Article in Proceedings |
| Conference | 2016 IEEE 13TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI) |
| MU Faculty or unit | |
| Citation | |
| Web | http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7493474 |
| Doi | http://dx.doi.org/10.1109/ISBI.2016.7493474 |
| Field | Informatics |
| Keywords | colon cancer; histopathology imaging; classification; gastrointestinal tract |
| Description | Molecular subtypes have been recently derived for various types of cancer, in an attempt to characterize the inter-tumoral heterogeneity. In this work we explore the possibility of constructing predictors for molecular subtypes based on histopathology images. For this, we introduce a novel 2-level bag-of-features method and we apply it to a collection of colorectal cancer samples. The resulting image features capture some relevant tumor morphology patterns and led to a classifier performing similarly to one constructed from features annotated by an expert pathologist. The significance of our results extends beyond subtype prediction since they demonstrate a possible approach to multimodal (histopathology and molecular) data mining and biomarker identification. |
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