Rashmi Kulkarni

Work place: Department of Information Science and Engineering, Dayananda Sagar College of Engineering, Bengaluru-560078,India.

E-mail: kulkarni.rashmi.25@gmail.com


Research Interests: Medical Image Computing, Computational Learning Theory, Artificial Intelligence


Mrs Rashmi Kulkarni received Bachelor of Engineering in Computer Science & Engineering in2016 and Master Degree M.Tech in computer Science and Engineering in 2018 from Visvesvaraya Technological University, Karnataka. Currently she is working as Technical Mentor in private institute. Her areas of interests are Medical Image Processing, Machine Learning, and Artificial Intelligence.

Author Articles
Analysis of CT DICOM Image Segmentation for Abnormality Detection

By Rashmi Kulkarni Bhavani K

DOI: https://doi.org/10.5815/ijem.2019.05.04, Pub. Date: 8 Sep. 2019

The cancer is a menacing disease. More care is required while diagnosing cancer disease. Mostly CT modality is used for Cancer therapy. Image processing techniques [1] can help doctors to diagnose easily and more accurately. Image pre-processing [2], segmentation methods [3] are used in extraction of cancerous nodules from CT images. Many researches have been done on segmentation of CT images with different algorithms, but they failed to reach 100% accuracy. This research work, proposes a model for analysis of CT image segmentation with filtered and without filtered images. And brings out the importance of pre-processing of CT images.

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