Concetti Chiave
An open-source tool for removing letters and adapting different color thresholds in HSV-colored medical images to enable robust computational image analysis using diverse multi-center data.
Sintesi
The authors developed an open-source tool in MATLAB to address the challenges of processing colored medical images for computational analysis. The key highlights are:
The tool can adapt different color thresholds of HSV-colored medical images, such as shear wave elastography images, to a reference image with a consistent color scale.
The tool can remove annotations and letters from the medical images, which are often added by clinicians for clinical interpretation but hinder automated image processing.
The tool was tested on a multi-center, international shear wave elastography dataset (NCT 02638935) with varying color thresholds across different centers and countries.
Step-by-step instructions with accompanying MATLAB code are provided, making the tool easy to follow and reproduce.
The open-source MATLAB tool is available at https://github.com/cailiemed/image-threshold-adapting, contributing to advancing medical image processing for developing robust computational imaging algorithms using diverse multi-center big data.
Statistiche
The maximum shear wave velocity setting in the dataset ranged from 0.5m/s to 10m/s across different centers.
The reference image had a maximum shear wave velocity of 10m/s.
The test image had a maximum shear wave velocity of 6.5m/s.
Citazioni
"Using colored medical images for AI-based analysis is a pressing issue. There are several applications where the interpretation of color-coded images is very challenging to the human eye, leading to inter-operator variability and limited diagnostic performance."
"We hope that this open-source tool contributes to advancing HSV medical image processing for developing robust computational imaging algorithms using diverse multi-center big data."