Abstract
The biomedical image segmentation is one of the challenging task and an interesting topic of research since a long time. In the field of biomedical image based disease analysis, automated segmentation methods plays a crucial role in fast and accurate disease analysis. It is also helpful to treat the at the early stage of a disease which often saves many lives. In this work, a new biomedical image segmentation method is proposed based on penalized fuzzy c-means coupled with level set method. The proposed method is tested on different types of biomedical images and some inspiring results are observed. Experimental results makes it suitable for the real life deployment in the diagnostic field to save some precious time for diagnostics.
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