Medical Imaging · GPU Visualization · AI Integration

AI-Powered Medical Imaging Workstation

Native C++ workstation for DICOM CT, MPR, GPU volume rendering, image processing and MONAI / ONNX segmentation.

DICOM CT → MPR / 3D → Processing → AI Inference → MPR / 3D Results

C++17Qt 6VTK 9.3DICOMGPU Volume RenderingONNX RuntimeMONAI

Watch 75-sec Demo ▶View GitHub ↗

AI Medical Imaging Workstation showing completed aorta segmentation, MPR views, 3D visualization and quantitative results

Overview

DICOM to AI Results

Medical Visualization

MPR · W/L · CT presets · GPU 3D volume rendering

Processing & Analysis

Measure · crop · segment · surface · volume

Medical imaging workstation overview with synchronized MPR and 3D CT visualization

Demo

75-Second Workflow

CT → MPR / 3D → AI → results.

Native AI Integration

MONAI runs through ONNX Runtime on a background QThread; the viewer stays interactive.

ONNX RuntimeBackground QThread105 Classes96³ Sliding Window

System Architecture

Medical Imaging + AI Pipeline

01 · InputDICOM CTLoad + validate

02 · ImagingMPR + GPU 3DVisualize + process

03 · PreprocessMONAIRAS · 3 mm · 96³

04 · InferenceONNX Runtime105 classes · CPU

05 · MappingAorta · Class 7Map to DICOM

06 · OutputMPR + 3DOverlay · surface · metrics

Native C++17 • Qt 6 • VTK • DICOM • ONNX Runtime • MONAI

Core Capabilities

Visualization, Processing & AI

Aorta segmentation shown with dimmed CT context

DICOM + MPRLoad · validate · navigate

GPU Volume RenderingInteractive 3D CT

Image ProcessingMeasure · crop · segment

Native AIMONAI · ONNX Runtime

DICOM MappingAI → source geometry

MPR + 3D ResultsOverlay · surface · metrics

AI Pipeline

Background Inference

AI inference running while the viewer remains interactive

MONAI Preprocessing + ONNX

RAS orientation + 3 mm isotropic preprocessing
96³ sliding-window inference with Gaussian blending
105-class segmentation through ONNX Runtime
Multiclass argmax → Aorta (Class 7)
Background QThread execution
Original DICOM geometry restoration

Reference Result

Quantitative Output

Completed AI aorta segmentation with quantitative results

53.70 cm³Aorta volume

1,971AI-grid voxels

27,805Source voxels

105Output classes

4Patches

~10 sInference

~30 sTotal pipeline

CPU + QThreadBackend

Visualization

MPR + 3D Result Modes

Aorta segmentation overlay in synchronized MPR views — MPR AI overlay mapped to the original DICOM geometry.

Aorta-only 3D AI surface — Aorta-only 3D surface mode.

Aorta AI surface with full CT context — Aorta + full CT anatomical context.

Technology Stack

Core Technologies

Native C++ medical imaging workstation running ONNX inference in a background QThread

C++17Application + AI

Qt 6UI + QThread

VTK 9.3MPR + volume rendering

vtk-dicomDICOM geometry

OpenGLGPU visualization

ONNX RuntimeNative inference

MONAICT segmentation

CMake / VS2022Build toolchain

Demo CT data: HEART_CT sample DICOM dataset from Fovia F.A.S.T. SDK demo cases. Imaging data is not redistributed.

Spatial Computing Extension

Medical Visualization on Apple Vision Pro

Apple Vision Pro Medical XR immersive CT workspace

Medical Imaging & AI Engineering

Need a DICOM / AI Integration?

DICOM Viewers GPU Volume Rendering AI Integration C++ / Qt / VTK

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