ARTIFICIAL INTELLIGENCE RECOMMENDATION SYSTEM FOR CANCER REHABILITATION SCHEME
Abstract :
Cancer is the most difficult problem in the field of medicine, and its postoperative recovery has become the most concerning problem for cancer patient. MRI is widely used for imaging technique to assess brain tumours, but the large amount of data produced by MRI needs manual segmentation in reasonable time, limiting the use of precise quantitative measurements in the clinical practice. So, automatic and reliable segmentation methods are required. Automatic segmentation is an challenging problem in which manual detection and segmentation of brain tumors using brain MRI scan forms a large part of human arbitration for detection and segmentation taken per patient, is both tedious and has huge internal and external observer detection and segmentation variability. Hence there is high demand for an efficient and automatic brain tumour detection and segmentation using brain MR images to be overcome errors in manual segmentation. In Practice, the system uses HSI (Hyper Spectral Imaging) to detect cancer cells. It is difficult to eliminate the ambiguities in MRI Brain samples. To overcome this difficulty, we are developing a system which detects the location of cancer cells into and out of MR Images and also suggests effective treatment like medications, vaccines, chemotherapy, etc. to physicians.
Keywords:
MRI, Automatic Segmentation, HSI
Citation: *,
( 2023), ARTIFICIAL INTELLIGENCE RECOMMENDATION SYSTEM FOR CANCER REHABILITATION SCHEME. Scientific Transactions in Environment and Technovation, 17(1): 10-17
Correspondence: Kavitha A