Fused Fuzzy Deep Learning and Information Steganography for Privacy Preservation in Medical Consumer Electronics

Jingxue Chen, Pengbiao Zhao, Erqiang Deng, Fazlullah Khan, Ryan Alturki, Bandar Alshawi, Hu Xiong

Research output: Journal PublicationArticlepeer-review

Abstract

—Medical Consumer Electronics (MCE) have greatly facilitated people’s lives, allowing patients to obtain personal medical information including medical images. These medical images obtained from MCE need to be processed using segmentation, diagnosis, recognition to obtain useful information. Deep learning plays an important role in medical image segmentation and recognition. However, other personal information about the patient, such as previous cases, is often required to determine the final diagnosis. However, sending personal information and medical images generated through MCE to the clinic directly exposes patient privacy. Therefore, in this paper, we propose a digital medical image privacy protection framework based on information steganography with fuzzy deep learning. The proposed framework transforms patient privacy information into invisible noise and hides it in the deep covert space of the image. This method plays a crucial role in ensuring patient privacy and data security. Furthermore, this method can ensure a high level of image segmentation accuracy that supports the development of personalized medical services. The experimental results show that the proposed framework can embed patient information in medical images without affecting the segmentation task, and effectively protect privacy. Finally, the proposed framework provides new possibilities and impetus for the popularization of MCE.

Original languageEnglish
JournalIEEE Transactions on Consumer Electronics
DOIs
Publication statusAccepted/In press - 2025

Keywords

  • Fuzzy Deep Learning
  • Information Steganography
  • Medical Consumer Electronics
  • Medical Image Segmentation
  • Privacy Protection

ASJC Scopus subject areas

  • Media Technology
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Fused Fuzzy Deep Learning and Information Steganography for Privacy Preservation in Medical Consumer Electronics'. Together they form a unique fingerprint.

Cite this