Cell Segmentation Using Multiple Instance Learning Based Support Vector Machines
2019 Medical Technologies Congress (TIPTEKNO)(2019)
Abstract
In this study, in order to perform cell segmentation on histopathological images, multiple instance learning (MIL) paradigm is applied. In this context, support vector machines adapted to multiple instance learning problems are utilized in the classification modelling. Then, during the test phase, the test images are scanned and classified at pixel level separately and presegmentation images are obtained. In the post processing step, the Markov random fields (MRA) method is applied to improve the pre-segmentation results. In the conclusion, the classification performances of multiple instance based support vector machines and the conventional support vector machines are given comparatively.
MoreTranslated text
Key words
Histopathological images,multiple instance learning,cell segmentation,markov random fields
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined