Pyramid-Focus-Augmentation: Medical Image Segmentation with Step-Wise Focus

TL;DR

This paper introduces a pyramid-like grid augmentation method for colon polyp segmentation, demonstrating its effectiveness and competitive performance in the Medico 2020 challenge.

Contribution

It proposes a novel step-wise focus augmentation technique using grid pyramids to improve medical image segmentation accuracy.

Findings

The method achieves results comparable to state-of-the-art approaches.

The pyramid augmentation enhances segmentation performance.

The approach is simple yet effective for gastrointestinal image analysis.

Abstract

Segmentation of findings in the gastrointestinal tract is a challenging but also an important task which is an important building stone for sufficient automatic decision support systems. In this work, we present our solution for the Medico 2020 task, which focused on the problem of colon polyp segmentation. We present our simple but efficient idea of using an augmentation method that uses grids in a pyramid-like manner (large to small) for segmentation. Our results show that the proposed methods work as indented and can also lead to comparable results when competing with other methods.