The article presents a new feature detection algorithm called centWave for high-resolution liquid chromatography coupled with mass spectrometry (LC/MS) data. The algorithm combines density-based detection of regions of interest (ROIs) in the m/z domain and a continuous wavelet transform (CWT) for chromatographic peak resolution. The authors evaluated the performance of centWave using two experiments with complex samples, including dilution series and mixtures of seed and leaf extracts from Arabidopsis thaliana. The results showed that centWave achieved higher F-scores compared to other algorithms, matchedFilter and centroidPicker from MZmine, indicating its superior sensitivity and precision in detecting features. The algorithm is available in the Bioconductor R-package XCMS and has been successfully used for LC-QTOF, LC-Orbitrap, and even CE-MS or GC-MS data.The article presents a new feature detection algorithm called centWave for high-resolution liquid chromatography coupled with mass spectrometry (LC/MS) data. The algorithm combines density-based detection of regions of interest (ROIs) in the m/z domain and a continuous wavelet transform (CWT) for chromatographic peak resolution. The authors evaluated the performance of centWave using two experiments with complex samples, including dilution series and mixtures of seed and leaf extracts from Arabidopsis thaliana. The results showed that centWave achieved higher F-scores compared to other algorithms, matchedFilter and centroidPicker from MZmine, indicating its superior sensitivity and precision in detecting features. The algorithm is available in the Bioconductor R-package XCMS and has been successfully used for LC-QTOF, LC-Orbitrap, and even CE-MS or GC-MS data.