Related papers: Deep classification algorithm for De-identificatio…
With the increase in Artificial Intelligence driven approaches, researchers are requesting unprecedented volumes of medical imaging data which far exceed the capacity of traditional on-premise client-server approaches for making the data…
With the wealth of medical image data, efficient curation is essential. Assigning the sequence type to magnetic resonance images is necessary for scientific studies and artificial intelligence-based analysis. However, incomplete or missing…
With the identity information in face data more closely related to personal credit and property security, people pay increasing attention to the protection of face data privacy. In different tasks, people have various requirements for face…
XNAT is a server-based data management platform widely used in academia for curating large databases of DICOM images for research projects. We describe in detail a deidentification workflow for DICOM data using facilities in XNAT, together…
Automated deidentification of clinical text data is crucial due to the high cost of manual deidentification, which has been a barrier to sharing clinical text and the advancement of clinical natural language processing. However, creating…
In numerous studies, deep learning algorithms have proven their potential for the analysis of histopathology images, for example, for revealing the subtypes of tumors or the primary origin of metastases. These models require large datasets…
X-ray imaging in DICOM format is the most commonly used imaging modality in clinical practice, resulting in vast, non-normalized databases. This leads to an obstacle in deploying AI solutions for analyzing medical images, which often…
Privacy protection has become a top priority as the proliferation of AI techniques has led to widespread collection and misuse of personal data. Anonymization and visual identity information hiding are two important facial privacy…
Digital Imaging and Communication System (DICOM) is widely used throughout the public health sector for portability in medical imaging. However, these DICOM files have vulnerabilities present in the preamble section. Successful exploitation…
De-identification of electronic health records (EHR) is a vital step towards advancing health informatics research and maximising the use of available data. It is a two-step process where step one is the identification of protected health…
The digitization of the medical data has been a sensitive topic. In modern times laws such as the HIPAA provide some guidelines for electronic transactions in medical data to prevent attacks and fraudulent usage of private information. In…
In this paper, we propose Hard Person Identity Mining (HPIM) that attempts to refine the hard example mining to improve the exploration efficacy in person re-identification. It is motivated by following observation: the more attributes some…
Image registration is a key task in medical imaging applications, allowing to represent medical images in a common spatial reference frame. Current approaches to image registration are generally based on the assumption that the content of…
Case-based explanations are an intuitive method to gain insight into the decision-making process of deep learning models in clinical contexts. However, medical images cannot be shared as explanations due to privacy concerns. To address this…
We report our effort to identify the sensitive information, subset of data items listed by HIPAA (Health Insurance Portability and Accountability), from medical text using the recent advances in natural language processing and machine…
As image processing systems proliferate, privacy concerns intensify given the sensitive personal information contained in images. This paper examines privacy challenges in image processing and surveys emerging privacy-preserving techniques…
Text de-identification techniques are often used to mask personally identifiable information (PII) from documents. Their ability to conceal the identity of the individuals mentioned in a text is, however, hard to measure. Recent work has…
Palmprint recognition techniques have advanced significantly in recent years, enabling reliable recognition even when palmprints are captured in uncontrolled or challenging environments. However, this strength also introduces new risks, as…
Internet users have been exposing an increasing amount of Personally Identifiable Information (PII) on social media. Such exposed PII can cause severe losses to the users, and informing users of their PII exposure is crucial to raise their…
Data protection methods like cryptography, despite being effective, inadvertently signal the presence of secret communication, thereby drawing undue attention. Here, we introduce an optical information hiding camera integrated with an…