• Priyanka Patil
• Prof. Vilas. S. Gaikwad

Automated segmentation of fine objects details in a given image is becoming of crucial interest in different imaging fields. In this work, we will propose a new variation level-set model for both global and interactive selective segmentation tasks, which can deal with intensity in homogeneity and the presence of noise. We will work on histopathological medical images. In this work, we will propose a new variation level-set model for both global and interactiveselective segmentation tasks, which can deal with intensity in homogeneity and the presence of noise. First we will check the presence of noise in input medical image. If the noise are present in given image then we will removed this noise using filtrations techniques. In addition, by using machine learning approach using Image segmentation using fuzzy entropy technique to segment the medical image. After that we will get the segmentation result in histopathological images.

Image segmentation, Median filter, Image noise, fuzzy entropy technique, machine learning;

"EFFICIENT METHOD OF NOISE REDUCTION AND SEGMENTATION OF MEDICAL IMAGES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.626-630, June-2019, Available :http://www.jetir.org/papers/JETIR1906D04.pdf

"EFFICIENT METHOD OF NOISE REDUCTION AND SEGMENTATION OF MEDICAL IMAGES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp626-630, June-2019, Available at : http://www.jetir.org/papers/JETIR1906D04.pdf