| Autor: |
Bodapalli, Nandan, Rao, Kunjam Nageswara, Prasad Dora, Parada Vara |
| Předmět: |
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| Zdroj: |
Indian Journal of Public Health Research & Development; Jul2019, Vol. 10 Issue 7, p438-443, 6p |
| Abstrakt: |
Use of computation techniques in medical research have progressed to a greater extend with the availability of higher order complex and accurate algorithms for detecting diseases. The medical diagnosis processes with human intervention cannot match with the demands from the consumers as the human process is slow and less accuracy as it completely depends on the skills of the individuals. One of the prominent medical diagnosis is detection of brain tumours cells. Human brain being the most important component of the body, can cause multiple other life-threatening diseases. These diseases are caused due to the presence of tumour in the brain cell. Hence, this research attempts to propose a higher accurate tumour detection algorithm. The improved accuracy is achieved due to the novel proposed dynamic intensity-based MR image enhancement algorithm and the proposed adaptive coefficient-based segmentation algorithm. Further, it is also been observed that, the presence of the tumour in the brain cortexes can lead to other diseases as well. These diseases from a large number of possibility space, can take a huge amount of time to diagnose and further propose medications. Hence a reduction of the possibility space and the reduced diagnosis process can give more time for medication to save the precious human life. Thus, yet another objective of this research is to automate the disease early prediction by recommending the diagnosis for reduced number of diseases by applying tumour centroid detection and mapping to human brain cortex functionalities. The work demonstrates a very high 97% accuracy for the detection and early prediction. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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