Towards Integrated Clinical-Computational Nuclear Medicine
Fuente:
arXiv
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| Autori principali: | , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866912726298656768 |
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| author | Farhadi, Faraz Esfahani, Shadi A. Yousefirizi, Fereshteh Luo, Monica Fernandez, Pedro Esquinas Sitek, Arkadiusz Sabet, Hamid Saboury, Babak Rahmim, Arman Heidari, Pedram |
| author_facet | Farhadi, Faraz Esfahani, Shadi A. Yousefirizi, Fereshteh Luo, Monica Fernandez, Pedro Esquinas Sitek, Arkadiusz Sabet, Hamid Saboury, Babak Rahmim, Arman Heidari, Pedram |
| contents | The field of Clinical-Computational Nuclear Medicine is rapidly advancing, fueled by AI, tracer kinetic modeling, radiomics, and integrated informatics. These technologies improve imaging quality, automate lesion detection, and enable personalized radiopharmaceutical therapy through physiologically based pharmacokinetic (PBPK) modeling and voxel-level dosimetry. Workflow automation and Natural Language Processing (NLP) further enhance operational efficiency. However, successful implementation and adoption of these tools require clinical oversight to ensure accuracy, interpretability, and patient safety. This paper highlights key computational innovations and emphasizes the critical role of clinician-guided evaluation in shaping the future of precision imaging and therapy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_18547 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards Integrated Clinical-Computational Nuclear Medicine Farhadi, Faraz Esfahani, Shadi A. Yousefirizi, Fereshteh Luo, Monica Fernandez, Pedro Esquinas Sitek, Arkadiusz Sabet, Hamid Saboury, Babak Rahmim, Arman Heidari, Pedram Medical Physics The field of Clinical-Computational Nuclear Medicine is rapidly advancing, fueled by AI, tracer kinetic modeling, radiomics, and integrated informatics. These technologies improve imaging quality, automate lesion detection, and enable personalized radiopharmaceutical therapy through physiologically based pharmacokinetic (PBPK) modeling and voxel-level dosimetry. Workflow automation and Natural Language Processing (NLP) further enhance operational efficiency. However, successful implementation and adoption of these tools require clinical oversight to ensure accuracy, interpretability, and patient safety. This paper highlights key computational innovations and emphasizes the critical role of clinician-guided evaluation in shaping the future of precision imaging and therapy. |
| title | Towards Integrated Clinical-Computational Nuclear Medicine |
| topic | Medical Physics |
| url | https://arxiv.org/abs/2511.18547 |