The dreadful disease considered is Oral carcinoma as is the 6th leading causes of death in rural -India. It can be treated and cured if detected early. The sureshot method of detecting carcinoma is biomedical Imaging Imaging hence plays a vital role in diagnosing,staging, and management of oral carcinoma.
This novel approach combines image preprocessing, feature extraction, and neural network design. Image analysis will be done on histopathological images (100samples)
This paper presents a computerized imaging technique (CT scan, MRI, PET scan along with histopathological samples- a carcinoma confirmatory test) to identify the visible and/ or palpable lesion of the lip, tongue or other oral cavity ulcers by extracting various discriminating features using Image processing and analyzing algorithms. These features along with
subjective symptoms are then applied to neural network ,which has been trained in such a way as to optimize and improve the decision making efficacy by continuous learning process.
The proposed system would help a professional to detect cancer in a short span of time with precise information taking assistance from the embedded artificial intelligence.
The results will be provided to the clinicians for approval. The proposed system will be refined from Radiologists, and Oncologists to obtain more precise decisions. This will hence prove to be useful in early detection of oral carcinomas.