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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.18963 |
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| _version_ | 1866913247956828160 |
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| author | Amartey, Ishmael N. Linninger, Andreas A. Ventimiglia, Thomas |
| author_facet | Amartey, Ishmael N. Linninger, Andreas A. Ventimiglia, Thomas |
| contents | Convolution and deconvolution are essential techniques in various fields, notably in medical imaging, where they play a crucial role in analyzing dynamic processes such as blood flow. This paper explores the convolution and deconvolution of arterial and microvascular signals for determining impulse and residue functions from in vivo or simulated data and the derivation of the relationship between the residue function and perfusion metrics such as the Cerebral Blood Flow (CBF), Mean Transit Time (MTT) and Transit Time to Heterogeneity (TTH). The paper presents the spectral derivatives as a technique for recovering the impulse response function from the residue function, detailing the computational procedures involved and strategies for mitigating noise effects. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_18963 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Quantification of Tracer Dilution Dynamics: An Exploration into the Mathematical Modeling of Medical Imaging Amartey, Ishmael N. Linninger, Andreas A. Ventimiglia, Thomas Image and Video Processing Spectral Theory Convolution and deconvolution are essential techniques in various fields, notably in medical imaging, where they play a crucial role in analyzing dynamic processes such as blood flow. This paper explores the convolution and deconvolution of arterial and microvascular signals for determining impulse and residue functions from in vivo or simulated data and the derivation of the relationship between the residue function and perfusion metrics such as the Cerebral Blood Flow (CBF), Mean Transit Time (MTT) and Transit Time to Heterogeneity (TTH). The paper presents the spectral derivatives as a technique for recovering the impulse response function from the residue function, detailing the computational procedures involved and strategies for mitigating noise effects. |
| title | Quantification of Tracer Dilution Dynamics: An Exploration into the Mathematical Modeling of Medical Imaging |
| topic | Image and Video Processing Spectral Theory |
| url | https://arxiv.org/abs/2402.18963 |