# Removal of Parameter Adjustment of Frangi Filters in Case of Coronary Angiograms

## TL;DR

This paper proposes a method to standardize Frangi Filter application on coronary angiograms by removing the need for manual threshold tuning, using image preprocessing techniques to handle illumination and enhancement.

## Contribution

The authors introduce a novel preprocessing pipeline that eliminates manual threshold adjustment for Frangi Filters across different fluoroscopes and patient data.

## Key findings

- Parameter tuning is no longer needed for different fluoroscopes.
- Preprocessing improves vessel enhancement consistency.
- Method verified on multi-hospital data.

## Abstract

Frangi Filters are one of the widely used filters for enhancing vessels in medical images. Since they were first proposed, the threshold of the vesselness function of Frangi Filters is to be arranged for each individual application. These thresholds are changed manually for individual fluoroscope, for enhancing coronary angiogram images. Hence it is felt, there is a need of mitigating the tuning procedure of threshold values for every fluoroscope. The current papers approach has been devised in order to treat the coronary angiogram images uniformly, irrespective of the fluoroscopes through which they were obtained and the patient demographics for further stenosis detection. This problem to the best of our knowledge has not been addressed yet. In the approach, before feeding the image to Frangi Filters, non uniform illumination of the input image is removed using homomorphic filters and the image is enhanced using Non Subsampled Contourlet Transform (NSCT). The experiment was conducted on the data that has been accumulated from various hospitals in India and the results obtained verifies dependency removal of parameters without compromising the results obtained by Frangi filters.