核磁共振光谱（MRS）是一种非侵入性的磁共振技术，能够提供组织生物化学信息。MRS已被广泛应用于脑瘤的研究，包括在术前和随访期间。在本研究中，我们调查了非负矩阵欠逼近（NMU）系列的多种变体的性能，其中包括稀疏NMU、全局NMU和递归NMU，并将它们与凸非负矩阵因子分解（C-NMF）进行了比较，前者曾经在使用MRS数据进行脑瘤诊断支持问题时表现良好。该调查有两个目的：首先，确定这些方法提取的源之间的差异；其次，比较每种方法在脑瘤分类诊断准确性中的影响，并将它们作为特征提取器使用。我们发现，首先，NMU变体在生物学可解释性方面找到了有意义的源，但与C-NMF相比，它们仅代表光谱的某些部分；其次，当一类病例不是脑膜瘤时，NMU方法在分类任务的分类准确性方面优于C-NMF。© 2023 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.

Magnetic resonance spectroscopy (MRS) is an MR technique that provides information about the biochemistry of tissues in a noninvasive way. MRS has been widely used for the study of brain tumors, both preoperatively and during follow-up. In this study, we investigated the performance of a range of variants of unsupervised matrix factorization methods of the non-negative matrix underapproximation (NMU) family, namely, sparse NMU, global NMU, and recursive NMU, and compared them with convex non-negative matrix factorization (C-NMF), which has previously shown a good performance on brain tumor diagnostic support problems using MRS data. The purpose of the investigation was 2-fold: first, to ascertain the differences among the sources extracted by these methods; and second, to compare the influence of each method in the diagnostic accuracy of the classification of brain tumors, using them as feature extractors. We discovered that, first, NMU variants found meaningful sources in terms of biological interpretability, but representing parts of the spectrum, in contrast to C-NMF; and second, that NMU methods achieved better classification accuracy than C-NMF for the classification tasks when one class was not meningioma.© 2023 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.