# Shaping the Future through Innovations: From Medical Imaging to Precision Medicine

arXiv: https://arxiv.org/abs/1605.02029 · HTML: https://mlsanity.com/paper/1605.02029/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 May 2016.

## Built on by (most cited first, 4 of 4)

- [Multi-Layer Gaussian Splatting for Immersive Anatomy Visualization](https://mlsanity.com/paper/2410.16978/) (2024)
- [ClipGS: Clippable Gaussian Splatting for Interactive Cinematic Visualization of Volumetric Medical Data](https://mlsanity.com/paper/2507.06647/) (2025)
- [XClipGS: Exact Half-Space Clipping for Medical Volume Gaussian Splatting](https://mlsanity.com/paper/2608.07760/) (2026)
- [BBR-Net: Boundary-Balanced Replay for Continual Medical Image Segmentation](https://mlsanity.com/paper/2606.14731/) (2026)

## Abstract (arXiv)

Medical images constitute a source of information essential for disease diagnosis, treatment and follow-up. In addition, due to its patient-specific nature, imaging information represents a critical component required for advancing precision medicine into clinical practice. This manuscript describes recently developed technologies for better handling of image information: photorealistic visualization of medical images with Cinematic Rendering, artificial agents for in-depth image understanding, support for minimally invasive procedures, and patient-specific computational models with enhanced predictive power. Throughout the manuscript we will analyze the capabilities of such technologies and extrapolate on their potential impact to advance the quality of medical care, while reducing its cost.