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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM62205
Volume:
10 |
4 |
April 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Amity Institute of information Technology
Amity university Raipur Chhattisgarh
Amity Institute of information Technology
Amity university Raipur Chhattisgarh
Amity Institute of information Technology
Amity university Raipur Chhattisgarh
Amity Institute of information Technology
Amity university Raipur Chhattisgarh
Amity Institute of information Technology
Amity university Raipur Chhattisgarh
Amity Institute of information Technology
Amity university Raipur Chhattisgarh
Today, medical image analysis has gained significant importance as it allows for accurate diagnosis of various illnesses at an early stage. In the present research, I propose the use of computer vision and deep learning methods for automatic detection of abnormalities based on X-ray and Magnetic Resonance Imaging (MRI) results. The proposed approach will be based on using convolutional neural networks (CNNs) for identifying relevant features in the analyzed medical images and their classification as abnormal or normal. In the research process, such steps as noise filtering, image normalization, and contrast optimization will be taken. Then, a deep learning algorithm will be used for recognizing abnormalities in images, including those of lungs, brain, and bones with the help of X-ray and MRI. In addition, transfer learning will be used to achieve higher precision by making use of pre-trained CNNs such as ResNet and VGG. It was evident from the results of experiments that the proposed method is extremely accurate, sensitive, specific and it can greatly help the medical experts. The proposed method will certainly aid in avoiding diagnostic mistakes, save time and contribute to improving patient’s health, particularly for patients living in areas where expert radiologists are scarce. The current study once again highlights the necessity of using artificial intelligence along with imaging techniques in designing diagnostic devices in future.
KEYWORDS
To begin with, it gives me great pleasure to thank my project guide and faculties who gave me their valuable guidance and support in conducting my research on “Medical Image Analysis for Disease Detection using X-Ray and MRI.” Secondly, I owe a lot to my school which has always been supportive in providing me with all the resources that I required during my research work. Furthermore, I am grateful to all my friends and fellow researchers who came forward in helping me in doing my project. Lastly, but by no means the least, I am thankful to my family members for always motivating and encouraging me.
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Publication Date
5/2/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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