naesView: A Secure and Intuitive Platform for Collaborative Medical Image Evaluation

Erik Nilsson, Attila Simkó

Keywords: Medical image evaluation, collaborative review platform, data-secure web viewer

TL;DR: We propose naesView: a lightweight, browser-based platform designed to facilitate collaborative evaluation of medical images while maintaining strict data security.

Abstract: Advances in artificial intelligence and imaging technologies are transforming medical research, creating new opportunities for collaboration between technical developers and clinical experts. However, these collaborations are often hindered by complex workflows, data-sharing restrictions and diverse software environments. naesView is a lightweight, browser-based platform designed to facilitate collaborative evaluation of medical images while maintaining strict data security. The system enables configurable, project-based review workflows without software installation or external data transfer. By keeping all image data local and only transmitting non-sensitive metadata, naesView minimizes regulatory overhead while supporting structured, reproducible image evaluations. This paper presents the system's architecture, design principles, and representative use cases demonstrating its practical utility in medical imaging research.

Primary Subject Area: Integration of Imaging and Clinical Data

Secondary Subject Area: Safe and Trustworthy Learning-assisted Solutions for Medical Imaging

Registration Requirement: Yes

Visa & Travel: Yes

Read CFP & Author Instructions: Yes

Originality Policy: Yes

Single-blind & Not Under Review Elsewhere: Yes

LLM Policy: Yes

Submission Number: 229