1. Review and potential for artificial intelligence in healthcare
- Author
-
Amit Sharma, Lina Sun, and Rajiv Kumar Gupta
- Subjects
education.field_of_study ,medicine.diagnostic_test ,Mri imaging ,Computer science ,business.industry ,Strategy and Management ,Population ,Brain tumor ,Magnetic resonance imaging ,Pattern recognition ,Image processing ,Image segmentation ,medicine.disease ,medicine ,Medical imaging ,Segmentation ,Artificial intelligence ,Safety, Risk, Reliability and Quality ,education ,business - Abstract
In the medical image analysis, recognition of tumor in brain is very important task and it leads cancer which should be diagnosed at early stage. It is an irregular cell population in brain and for the cancer diagnosis; medical imaging techniques play an important role. The mostly used and efficient technique for the segmentation is Magnetic resonance imaging (MRI). There is huge progress the field of MRI imaging technique for accessing the brain injury and the brain anatomy exploring. The segmentation and detection of the tumor from the MRI images are done by the image processing techniques. Manual detection of brain tumor is the complex task, so the different image segmentation methods are developed for detection and segmentation of the tumor from the MRI images. The various recent brain tumor segmentation techniques are thoroughly discussed in this paper. The quantitative analysis of existing techniques and the performance evaluation is done and detailed. The paper revealed different image segmentation methods are briefly discussed. This survey article provides the detailed information of the different segmentation methods along with their merits and demerits. Effectiveness of the methods is shown in terms of the performance parameters.
- Published
- 2021