ICSES Transactions on Image Processing and Pattern Recognition

Vol. 5, No. 2, Jun. 2019

Research Directions and Future Trends in Medical Image Segmentation | Miscellaneous

Vikramsingh Parihar a,, Hamid Reza Boveiri b
a PRMCEAM, Amravati, India
b Sama College, IAU, Shoushtar Branch, Shoushtar, Iran

Highlights and Novelties

1- This editorial article discuses the evolution of medical image segmentation techniques.

2- The article ends with the discussion on the future trends and directions in this field.

3- In this article, some approaches are briefly discussed and compared.

4- Deep learning methods have also been included.

Manuscript Abstract
In the recent years, medical image analysis has turned to be the center of attention for the researchers and practitioners all over the world as it provides high-fidelity and minimally-invasive means for diagnosis, prognosis, therapy and follow-up procedures. Medical image processing techniques in the literature are concentrated vastly on the important processes of filtering, enhancement and object detection, and a variety of methods proposed to improve the image quality for both visual perception and feature detection where the image segmentation is indeed one of the most attractive yet complicated techniques. In this article, a brief updating on computational advances applied to medical image segmentation is provided along with the discussion of some popular methodologies for related medical image processing techniques.

 Deep Learning   Image Analysis   Image Processing   Image Segmentation   Medical Imaging 

© Copyright was transferred to International Computer Science and Engineering Society (ICSES) by all the Authors.

Cite this manuscript as
Vikramsingh Parihar, Hamid Reza Boveiri, "Research Directions and Future Trends in Medical Image Segmentation," ICSES Transactions on Image Processing and Pattern Recognition (ITIPPR), vol. 5, no. 2, pp. 1-3, Jun. 2019.

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