Insights & Research
Technical deep dives, clinical AI research updates, and insights from the Salnus team.
Meniscus Tear Detection with AI: Why Detection Outpaces Localisation in Knee MRI
AI detects meniscal tears with 87% sensitivity — but accurately localising them remains a challenge. How deep learning is advancing meniscus assessment, where the gaps are, and what clinicians should know about the detection-localisation asymmetry.
AI Fracture Detection: How Deep Learning Is Reducing Missed Fractures in Emergency Radiology
Emergency departments miss 3–9% of fractures on initial radiograph interpretation. AI-powered fracture detection systems are demonstrating sensitivity improvements from 81% to 92% — here's what clinicians need to know about the technology, commercial tools, and clinical evidence.
AI in Paediatric Orthopaedics: Why Personalised 3D Planning Is Critical for Growing Bones
Children are not small adults — their growing bones demand surgical precision that generic templates cannot provide. How AI-powered 3D planning, patient-specific instrumentation, and predictive modelling are transforming paediatric deformity correction, DDH screening, and fracture management.
From CT Scan to 3D Model: How AI Bone Segmentation Is Changing Surgical Planning
How deep learning transforms CT scans into patient-specific 3D bone models in minutes — replacing hours of manual segmentation and enabling precision surgical planning for knee osteotomy, arthroplasty, and complex reconstruction.
AI in Orthopaedics: A Guide for Surgeons in Turkey (2026)
Comprehensive guide to AI applications in orthopaedic surgery with focus on Turkey's regulatory framework — TİTCK, ÜTS registration, TÜSEB/TÜBİTAK funding, and clinical adoption.
Preoperative Planning Software in Orthopaedic Surgery: A 2026 Guide
A practical guide to modern preoperative planning software for orthopaedic surgery — from 2D templating to AI-powered 3D reconstruction, and what features matter for clinical workflow.
AI in Orthopaedic Surgery: Where We Stand in 2026
Comprehensive guide to AI in orthopaedic surgery — radiographic OA grading, MRI ligament analysis, 3D surgical planning, robotics, regulatory landscape, and privacy architecture.
How to Choose an AI Tool for Knee OA Assessment
A practical evaluation framework for orthopaedic surgeons comparing AI-powered knee osteoarthritis grading tools — what to ask vendors, which metrics matter, and red flags to watch for.
The Forgotten Ligament: Why PCL Lags Behind ACL in AI Research
Of 29 deep learning studies on cruciate ligament injury detection, only one addresses the PCL. Why the posterior cruciate ligament remains AI's blind spot — and what needs to change.
ACL Injury Assessment with AI: MRI to Decision Support
Deep learning for ACL tear detection from knee MRI — automated assessment, severity grading, surgical outcome prediction, and clinical deployment.
AI in Hip OA: Where Deep Learning Meets Clinical Need
AI in hip osteoarthritis — radiographic classification, progression prediction, and Salnus's PROSPERO-registered systematic review.
Best DICOM Viewers for Orthopaedic Surgeons (2026)
Comparing DICOM viewers for orthopaedic surgeons — free tools, desktop apps, and AI-integrated platforms with automated measurements.
AI-Powered OA Screening: X-Ray to Clinical Insight
How deep learning screens for knee OA from radiographs — model architecture, training on OAI data, and clinical integration at Salnus.
What Is DICOM? A Guide to Medical Imaging Standards
DICOM for orthopaedic surgeons — the universal standard behind every CT, MRI, and X-ray, and what clinicians need to know.
Kellgren-Lawrence Grading System: A Complete Guide
The KL grading system for knee OA — radiographic criteria, clinical interpretation, inter-observer variability, and AI-assisted grading.
How to Read a Knee X-Ray: A Systematic Approach
Systematic knee radiograph interpretation — technical adequacy, bone assessment, joint space, soft tissue, alignment, and clinical correlation.
Why Orthopaedic AI Needs Surgeon-Engineer Collaboration
Why pure-tech teams fail in medical AI and how surgeon-engineer collaboration from day one produces better orthopaedic AI models and outcomes.
Building a Medical AI Startup in Turkey
Building an orthopaedic AI startup in Istanbul — architecture decisions, regulatory navigation, and Turkey's medical AI ecosystem.
Patient-Specific Guides for Knee Reconstruction (OJSM)
Our OJSM-published study validating 3D-printed patient-specific instrumentation for knee reconstruction — clinical accuracy and workflow.
GradCAM Explained: AI Visualisation in Medical Imaging
How GradCAM works, why it matters for clinical trust in medical AI, and what the heatmaps reveal when overlaid on a knee radiograph.
3D-Printed Surgical Guides: CT Scan to Operating Room
Patient-specific 3D-printed surgical guides — design workflow, clinical evidence, material selection, and AI-accelerated production.
Knee OA Progression: From Early Changes to End-Stage Disease
Knee OA stages from pre-radiographic disease to end-stage — risk factors, treatment at each stage, and AI-assisted progression monitoring.
Privacy by Design: Client-Side Medical AI Processing
Client-side AI for medical imaging — browser-based inference, KVKK/HIPAA compliance, and why architecture is the privacy strategy.
Mechanical Axis Alignment: LDFA, MPTA, HKA Explained
Lower limb alignment for orthopaedic surgeons — LDFA, MPTA, HKA, FTA measurement, normal values, and role in OA and surgical planning.
DICOM vs JPEG: Why File Format Matters in Medical Imaging
DICOM vs JPEG for medical imaging — why JPEG loses critical clinical data and how DICOM preserves diagnostic fidelity for surgeons.
Joint Space Width in Knee OA: Techniques and Values
JSW measurement in knee OA — standardised techniques, normal reference values, common pitfalls, and AI-assisted reproducibility.