Medical Image Segmentation : A Comparative Study and Survey

Ruchi Bhardwaj; Shanu Gour

doi:10.32628/IJSRSET24115104

Authors

Ruchi Bhardwaj M.Tech Scholar, Bharti Vishwavidyalaya, Durg, Chhattisgarh, India Author
Shanu Gour Assistant Professor (CSE), Bharti Vishwavidyalaya, Durg, Chhattisgarh, India Author

DOI:

https://doi.org/10.32628/IJSRSET24115104

Keywords:

Medical Image Processing , Medical Diagnosis, Methods and Applications

Abstract

Image segmentation involves dividing an image into distinct segments. It is important to distinguish this from image enhancement, which focuses on improving the image’s visual attributes, such as brightness, contrast, and texture. In segmentation, specific parts of the image are emphasized based on the problem being addressed. Clinical imaging techniques are continuously evolving, aiming to improve the quality of services in the healthcare industry. Methods such as interpolation, image registration, compression, and diagnosis need to be updated to meet the increasing demands of the field, especially with advancements in mobile and cloud computing technologies. The integration of medical devices with wearable technologies presents a promising area for further exploration. This paper provides valuable insights into the domain of medical imaging systems and aims to outline the future potential of work in this field.

Downloads

Download data is not yet available.

References

Dr. Nookala Venu”: Medical Image Segmentation Using Soft Computing Techniques”, 2022IUSST.

Risheng” Medical image segmentation using deep learning: A survey” 2021 IET.

Dr. S. Priyadarsini, S. Chitra, K. Pushpadevi, “Medical Image Processing Using Deep”, 2022 IJCRT.

B. Nemade, S. S. Alegavi, N. B. Badhe, and A. Desai, “Enhancing information security in multimedia streams through logic learning machine assisted moth-flame optimization,” ICTACT Journal of Communication Technology, vol. 14, no. 3, 2023. DOI: https://doi.org/10.21917/ijct.2023.0449

S. S. Alegavi, B. Nemade, V. Bharadi, S. Gupta, V. Singh, and A. Belge, “Revolutionizing Healthcare through Health Monitoring Applications with Wearable Biomedical Devices,” International Journal of Recent Innovations and Trends in Computing and Communication, vol. 11, no. 9s, pp. 752–766, 2023. [Online]. Available: https://doi.org/10.17762/ijritcc.v11i9s.7890. DOI: https://doi.org/10.17762/ijritcc.v11i9s.7890

Masoud Khani,” Medical Image Segmentation Using Machine Learning” UWM 2021

Aarish Shafi, “Medical Image Segmentation A Review of Recent Techniques, Advancements and a Comprehensive Comparison”. IJCSE 2019

Akshay Kumar S, “Medical Image Classification and Cancer Detection using Deep Convolution Networks” IJERT 2021.

Gagandeep k “A Survey on Medical Image Segmentation” PIMCSIT 2017.

Sriparna Saha “Brain image segmentation using semi-supervised clustering” IJCSIT 2016. DOI: https://doi.org/10.1016/j.eswa.2016.01.005

Manvel Avetisian “Volumetric Medical Image Segmentation with Deep Convolution Neural Networks” ITCSCP 2022.

Saima Anwar Lashari “A Framework for Medical Image Classification Using Soft Set” ICEEI 2013 DOI: https://doi.org/10.1016/j.protcy.2013.12.227

Bingquan Huo “Medical and Natural Image Segmentation Algorithm using M-F based Optimization Model and Modified Fuzzy Clustering: A Novel Approach.” IJSPIPPR 2015.

Ashraf A. Aly “RESEARCH REVIEW FOR DIGITAL IMAGE SEGMENTATION TECHNIQUES” IJCSIT 2011.

Sujata Saini “Analysis on the Different Image Segmentation Techniques” IJICT 2014.

M. Rastgarpour “Application of AI Techniques in Medical Image Segmentation and Novel Categorization of Available Methods and Tools” IMECS 2011.

Dilpreet Kaur “Various Image Segmentation Techniques” IJCSMC 2014.

Divya Kaushik “Medical Image Segmentation using Genetic Algorithm” IJCA 2013. DOI: https://doi.org/10.5120/14222-2220