AI Based Nanorobot Assisted Endoscopic Imaging For Early Detection Of Gastric Disorders

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dc.contributor.authorChandresh M 1NH22CS054
dc.contributor.authorPatan Izaz Khan 1NH22CS281
dc.contributor.authorAgnes Arul 1NH22EC006
dc.contributor.authorAkshayaasri S 1NH22EC009
dc.date.accessioned2026-02-09T09:02:35Z
dc.date.available2026-02-09T09:02:35Z
dc.date.issued2026-02-09
dc.description.abstractThis project introduces a comprehensive intelligent system designed for the early identification of gastric disorders through AI-driven CT image analysis, paired with a prototype for drug delivery inspired by nanorobotics. The early detection of stomach tumors can be quite difficult due to the subtlety of symptoms and the intricacies involved in manually interpreting CT images. To bridge this gap, the proposed model utilizes a Convolutional Neural Network (CNN) created with Python 3.13 and TensorFlow, which automatically classifies CT images of the stomach and accurately identifies potential tumor regions. The system employs sophisticated image preprocessing methods, including noise reduction, contrast enhancement, and normalization, to enhance diagnostic reliability.
dc.identifier.urihttp://192.168.75.5:4000/handle/123456789/21001
dc.titleAI Based Nanorobot Assisted Endoscopic Imaging For Early Detection Of Gastric Disorders
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