ITKIT: Feasible CT Image Analysis based on SimpleITK and MMEngine

TL;DR

ITKIT is a user-friendly, configurable framework for CT image analysis that streamlines the process from DICOM data to 3D segmentation, suitable for users with varying computing resources.

Contribution

The paper introduces ITKIT, a comprehensive and accessible pipeline for CT image analysis that integrates existing frameworks and simplifies deployment for diverse user needs.

Findings

ITKIT successfully supports basic CT analysis scenarios.

The framework is easy to use for users with limited computing power.

ITKIT's flexible configuration benefits advanced users.

Abstract

CT images are widely used in clinical diagnosis and treatment, and their data have formed a de facto standard - DICOM. It is clear and easy to use, and can be efficiently utilized by data-driven analysis methods such as deep learning. In the past decade, many program frameworks for medical image analysis have emerged in the open-source community. ITKIT analyzed the characteristics of these frameworks and hopes to provide a better choice in terms of ease of use and configurability. ITKIT offers a complete pipeline from DICOM to 3D segmentation inference. Its basic practice only includes some essential steps, enabling users with relatively weak computing capabilities to quickly get started using the CLI according to the documentation. For advanced users, the OneDL-MMEngine framework provides a flexible model configuration and deployment entry. This paper conducted 12 typical experiments to verify that ITKIT can meet the needs of most basic scenarios.