Computer Assisted Isolation of Cancerous cell from Neuroblastoma Histology using Image Segmentation Methods

Computer Assisted Isolation of Cancerous cell from Neuroblastoma Histology using Image Segmentation Methods

           Bhavya Sharma1, Jhanvi Garg 2 , Kunal Chakraborty3 ,  Ishaan Joshi4

B.Tech Student1,2,3,4

Department of Computer Science and Engineering Inderprastha Engineering College, Sahibabad, Ghaziabad, India

Abstract:
Neuroblastoma is the third most common type of childhood cancer in the pediatric age group. It is a type of cancer that is found in the adrenal glands present above the kidney. It usually affects the particular regions such as stomach, chest, neck, pelvis, and bones. Children are usually diagnosed with Neuroblastoma cancer between the age of 1 to 2 year. It can be discovered by certain imaging techniques. Imaging is one of the crucial techniques in the diagnosis, staging, treatment planning, response evaluation, and follow-up of a Neuroblastoma case. The current prognostic classification of this disease is based in part on the morphological characteristics of the cells as seen in the images stained with H&E (Hematoxylin and eosin). The main goal is to detect the cancer cells from the H&E-Stained images by applying color segmentation, cell extraction, boundarization & major minor axis detection.

Keywords:

H&E-stained images, Neuroblastoma, Segmentation, image analysis, Machine learning, Medical image processing.