Smoother

We use this to denoise inherently noisy MSI datasets, from a choice of 3 different smoothing methods. The smoothing methods supported are Savitzky-Golay, Moving Mean, and Triangular Moving Mean. Once a spectrum is smoothed, we remove negaitves so that all negative values are equal to zero.

Options

Smoothing Method

Savitzky-Golay: If chosen, the intensity of a spectrum will be smoothed using Savitzky-Golay smoothing. This is the industry standard or smoothing in MSI.
Moving Mean: If chosen, the intensity of a spectrum will be smoothed using the Moving Mean.
Triangular Moving Mean: If chosen, the intensity of a spectrum will be smoothed using the Triangular Moving Mean.

Input Ports

: The incoming data should contain rows spectra m/z values.
: The incoming data should contain rows spectra intensity values.

Output Ports

: The outgoing data is exactly equal to the incoming rows of spectra m/z values from incoming port 0.
: The outgoing data consists of the rows of smoothed spectra Intensity values.

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Installation

To use this node in KNIME, download the below referenced file, save it to your KNIME's plugin folder and restart KNIME.

v5.5

Plugin provider:

Plugin version: 1.0.1

On NodePit since: 2025-07-02

Last update: 2025-07-26

KNIME versions: Since v3.6

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