Keywords: Quantitative Imaging, RelaxometryQuantitative analysis of T1 spectra could reveal microscopic properties and have been used to study biological tissues such as the heart, brain and related disease. It is challenging to determine the relaxation times from magnetic resonance signals particularly with multicomponent continuous spectra as it is an inherently ill-posed exponential analysis problem even with a large number of input data points. Artificial neural networks have been trained to determine T1 spectra with 8 to 4 logarithmically spaced data points. Improved performance over a larger range of T1 values and faster processing time compared to traditional methods have been achieved.
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