GPU-Powered AI
Intelligence for Radiology

A unified compute and AI platform — deep-learning segmentation, measurement, and image enhancement for every CT and MR study, out of the box.

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Everything Radiology AI Needs,
In One Platform

A unified compute and AI layer — GPU-accelerated inference, multi-organ segmentation, and image enhancement, all out of the box.

12+
AI Models Onboard
92%
Clinical Sensitivity
<1s
Inference per Study
0
New Hardware Required

Optimized GPU Hardware

Purpose-configured GPU nodes for medical AI inference — sub-second results across concurrent studies, zero bottlenecks.

Unified AI Orchestration

Single layer managing model deployment, study routing, inference scheduling, and result delivery across your entire network.

AI Enhancement — CT & MR

Deep-learning reconstruction improves SNR and sharpness — enabling better downstream detection without re-scanning.

Multi-Organ Segmentation

Automated segmentation of Brain, Lung, Liver, Spleen, Pancreas and more — as structured DICOM overlays, instantly.

Quantitative Measurements

Precision volumetric measurements for organs, Body Fat, and BMD — automated, reproducible, and reportable.

DICOM & PACS Native

Plug-and-play with any PACS, RIS, or scanner via native DICOM — zero proprietary connectors required.

Aiken AI Platform Features
Aiken AI Platform™ — At a Glance
Deployed across India, USA & Australia
GPU Inference Speed<1s
Clinical Sensitivity92%
Scanner Compatibility95%
SNR Improvement+70%
ISO 13485 HIPAA Compliant FDA Registered DICOM Native

From DICOM Ingestion to Structured AI Output

A seamless, automated pipeline — scan arrives, AI runs, results land in your PACS. No manual steps required.

Step 1
DICOM Study Ingestion
Scans arrive via DICOM push or pull from any scanner or PACS. The platform automatically identifies modality, body region, and priority.
Any scanner
Step 2
AI Enhancement & Pre-processing
Deep-learning reconstruction improves image quality — boosting SNR, correcting artefacts, normalising contrast for consistent AI performance.
+70% SNR
Step 3
GPU Model Inference
Segmentation, measurement, and detection models run in parallel on dedicated GPU hardware — returning results in under one second.
<1s inference
Step 4
Results & PACS Push
AI findings packaged as DICOM SR overlays and structured reports, automatically pushed to your PACS ready for radiologist review.
DICOM SR

GPU Compute

Purpose-built inference nodes

Optimised

Inference Speed

Per study, end-to-end

<1 Second

AI Models

Independently deployable modules

12+ Models

Clinical Sensitivity

Multi-centre validated algorithms

92% Accuracy

Specialized Clinical Modules

Each module is independently deployable and pre-validated on multi-centre clinical datasets.

Neuro & Spine Module

Brain MRI · Spine MRI · Stroke pathway

Brain tumour segmentation & volumetry
White matter lesion detection
Vertebral fracture classification
StrokeSuite: CTA perfusion analysis
Brain atrophy quantification

Chest & Oncology Module

CT Chest · OncoSuite · Nodule AI

Lung nodule detection & Lung-RADS classification
Pleural effusion quantification
Tumour response assessment (RECIST)
Chest X-ray triage — 14 findings
COPD / emphysema scoring

Body Composition Module

Aiken Adipo · Aiken BMD

Visceral & subcutaneous fat quantification
Skeletal muscle mass — sarcopenia index
Bone Mineral Density (BMD) scoring
Liver, Spleen & Pancreas volume
Automated thigh MRI body composition

Image Enhancement Module

CT · MR · GAN Reconstruction

GAN-based MRI super-resolution & denoising
Low-dose CT reconstruction (LDCT)
Motion artefact correction
Multi-organ MRI segmentation improvement
Compatible with 1.5T & 3.0T scanners
Version 1.3.80| CDSCO MD-5 [MFG/MD/2024/000597]| QuickSuite is intended for use by, or under the supervision of, licensed healthcare professionals only| contact@aikenist.com| +91 7560898983