# Artificial intelligence for simplified patient-centered dosimetry in radiopharmaceutical therapies

arXiv: https://arxiv.org/abs/2510.12714 · HTML: https://mlsanity.com/paper/2510.12714/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 153 references that are in the map.
- First posted on arXiv 14 Oct 2025.

## Builds on (most cited first, 7 of 7)

- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [TotalSegmentator: robust segmentation of 104 anatomical structures in CT images](https://mlsanity.com/paper/2208.05868/) (2022)
- [PET image denoising based on denoising diffusion probabilistic models](https://mlsanity.com/paper/2209.06167/) (2022)
- [A task-specific deep-learning-based denoising approach for myocardial perfusion SPECT](https://mlsanity.com/paper/2303.00212/) (2023)
- [Learning Fuzzy Clustering for SPECT/CT Segmentation via Convolutional Neural Networks](https://mlsanity.com/paper/2104.08623/) (2021)
- [How to Segment in 3D Using 2D Models: Automated 3D Segmentation of Prostate Cancer Metastatic Lesions on PET Volumes Using Multi-angle Maximum Intensity Projections and Diffusion Models](https://mlsanity.com/paper/2407.18555/) (2024)
- [A Generalizable 3D Diffusion Framework for Low-Dose and Few-View Cardiac SPECT](https://mlsanity.com/paper/2412.16573/) (2024)

## Abstract (arXiv)

KEY WORDS: Artificial Intelligence (AI), Theranostics, Dosimetry, Radiopharmaceutical Therapy (RPT), Patient-friendly dosimetry KEY POINTS - The rapid evolution of radiopharmaceutical therapy (RPT) highlights the growing need for personalized and patient-centered dosimetry. - Artificial Intelligence (AI) offers solutions to the key limitations in current dosimetry calculations. - The main advances on AI for simplified dosimetry toward patient-friendly RPT are reviewed. - Future directions on the role of AI in RPT dosimetry are discussed.