Himanshu Pawar

Work place: Instrumentation Engineering Department, Vishwakarma Institute of Technology, Pune, India

E-mail: himanshu.pawar19@vit.edu

Website: https://orcid.org/0009-0002-5906-8651

Research Interests:

Biography

Himanshu Pawar is an undergraduate student at Department of Instrumentation Engineering, Vishwakarma Institute of Technology Pune.

Author Articles
CNN and GAN Based Stroke Detection Using CT Scan Images

By Archana Chaudhari Atharva Rajadhyaksha Sharvil Patil Himanshu Pawar

DOI: https://doi.org/10.5815/ijigsp.2025.02.06, Pub. Date: 8 Apr. 2025

The objective of the research work is to detect stroke using CT scan images. In the research work an analysis of 3D CNN method for stroke detection is presented. The work also presents a new method of stroke detection using semi-supervised Adversarial Networks (SGAN).3D CNN is the traditional approach to any type of image classification problem. But being data-hungry, it becomes difficult to use them when data is scarce. High-quality medical data is difficult to find and hence alternative approaches seem worth approaching. The relatively new GANs can generate images like the training images, and its SGAN variant can use these generated images for training the classifier. We investigate the usefulness of SGANs comparatively with CNNs in this paper. The proposed SGAN method is compared with state of art methods in literature using accuracy, sensitivity and specificity. The SGAN method demonstrates an accuracy of 93%, Sensitivity of 100% and Specificity of 90%. For small data sets in medical imaging the proposed SGAN method exhibit an encouraging performance as compared to other methods using large datasets. In the research paper, we propose methodologies for detecting strokes by using 2 approaches: 3D CNNs and SGANs. The relatively new GANs can generate images like the training images, and its SGAN variant can use these generated images for training the classifier. We investigate the usefulness of SGANs comparatively with CNNs in this paper.

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