An Optimized Super Pixel Based Clustering Algorithm for Histopathalogical Images of Cancer
The process of examining tissues under a microscope for detecting the severity of the disease is called histology, it became very critical in biomedical research and clinical practice. Processing tissues from histopathological images has become now fully computerized, the labs can produce tissue slides for viewing images digitally. pathologist examine these digital images on a computer rather than on microscope inorder predict the seriousness of cancer. Routine analysis of tissues selection will be very difficult, manual task can be done only by trained pathologists at a huge cost. Hence cell nuclei recognition and classification plays a vital role in early diagnosis of cancer. It is a very difficult task, due to heavy noise, and small-variant sizes of cell nuclei in histology images.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.