Instant3D: A Lightweight Open-Source GUI Frontend for TotalSegmentator-Based Medical Image Segmentation and 3D Reconstruction

Automatic segmentation is increasingly used in medical imaging, but many tools require command-line operation and environment setup. TotalSegmentator provides open-source multiorgan segmentation for computed tomography (CT) and magnetic resonance imaging (MRI) data, yet its routine use may be challenging for nontechnical users. Herein, we describe the design, implementation, and functionality of Instant3D, a lightweight, open-source graphical user interface (GUI) frontend for TotalSegmentator. Instant3D was developed in Python using PyQt6. It accepts DICOM folders, NIfTI files, and NRRD files as input and allows users to select regions of interest (ROIs) through a suggestion-enabled interface. The GUI executes TotalSegmentator as the backend. Default outputs include STL meshes for 3D visualization and NIfTI segmentation images, with optional SVG masks and CSV files containing volumetric measurements. SVG masks are interoperable with SegRef3D for slice-level review and refinement of automated segmentation results. Batch processing is supported. Functionality was tested using representative CT and MRI datasets. Instant3D successfully imported supported formats, executed TotalSegmentator through the GUI, and generated expected outputs, including STL, NIfTI, SVG, and CSV files. Representative datasets demonstrated successful workflow completion and compatibility with SegRef3D. Batch processing generated organized output files for multiple input datasets, confirming workflow feasibility. Instant3D simplifies TotalSegmentator execution and facilitates generation of reusable 3D reconstruction outputs. While not a replacement for comprehensive visualization platforms, it complements them by providing a streamlined workflow for ROI selection, batch processing, and multiformat export. Instant3D may serve as a practical tool for research, education, quantitative imaging, and 3D model generation.