Research work on Digital Healthcare

Security Framework for Medical Data

Abstract: IoT and healthcare create an intelligent hospital ecosystem. This ecosystem must protect medical data. This paper presents a new yet easy security paradigm for IoT hops to secure medical data. Encryption protects the proposed structure. Images are scrambled by spiralizing the medical data matrix, matrix exponential diffusion, and sequential chaotic map pseudorandom number generation. Eventually, a reliable decryption technique recovers the data. The proposed architecture is efficient and durable, making it suitable for the IoT environment, according to experiments.

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Journal Paper

Automatic Classification of Diabetic Retinopathy Images

Abstract: Diabetic retinopathy (DR) is a significant reason for the global increase in visual loss. Studies show that timely treatment can significantly bring down such incidents. Hence, it is essential to distinguish the stages and severity of DR to recommend needed medical attention.

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Conference Paper Journal Paper

Medical Image Segmentation Tool (MIST)

Abstract: In order to obtain the most suitable method for medical image segmentation, we propose MIST (Medical Image Segmentation Tool), a two stage algorithm. The first stage automatically generates a binary marker image of the region of interest using mathematical morphology. This marker serves as the mask image for the second stage which uses GrabCut to yield an efficient segmented result. The obtained result can be further refined by user interaction.

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Project Paper