We serve healthcare needs through six pillars.
Medical device software powered by cutting-edge deep learning. Analyzes medical images with high precision, delivering real-time insights and explainable results that physicians can trust.
Free white paper (in Japanese)Medical Diagnostic Support AI: Its Potential and LimitsDownloadRemote image interpretation by specialist physicians. Delivering high-quality radiology reports in a timely manner regardless of location, helping bridge regional gaps in healthcare access. Our platform architecture, built for the future implementation of an AI inference engine, enables a smooth expansion to advanced AI-powered cloud radiology services.
A cloud-based electronic health record. With an optional integration with our Cloud Radiology Services, even facilities without an on-site radiologist can go from imaging orders to radiology reports entirely within the record.
A managed service providing high-quality data annotation by specialist physicians and domain experts. Through a multi-stage quality assurance process, we build expertly curated datasets that support pharmaceutical R&D, drug discovery, and AI development.
Generating rich structured datasets from medical images. Partnering with pharmaceutical companies to accelerate drug discovery and R&D with high-quality AI-analyzed clinical data and quantitative biomarkers.
Custom AI model and system development. Building tailored solutions from concept to deployment for your unique challenges.
Learn moreOur AI Medical Diagnostic SaMD covers four clinical domains:
ophthalmology, gastroenterology, orthopedics, and neurology.
Grounded in deep clinical expertise across each area, we deliver solutions that address real clinical needs.
AI-powered diagnostic support systems for retinal diseases using OCT (Optical Coherence Tomography) and fundus photographs. Our system detects major retinal conditions that can lead to vision loss with high accuracy, supporting ophthalmologists in their diagnostic workflow.
Automated analysis of retinal layer structures and disease classification. Detects over 10 types of retinal findings with high accuracy.
Fundus photograph-based diabetic retinopathy severity classification (Davis classification) and lesion segmentation. Automatically detects hemorrhages, exudates, neovascularization, and other pathological findings.
Beyond the presence or absence of disease, we also address severity and progression assessment—for example, staging of diabetic retinopathy (Stage 1–4), among other staged evaluations of major conditions.
Automatically extracts a range of OCT findings (such as subretinal fluid (SRF) and layer-structure abnormalities), with per-finding color coding and tagging.
An integrated AI diagnostic support system using CT imaging that covers two areas: the hepatobiliary-pancreatic organs (liver, biliary tract, pancreas) and the gastrointestinal tract (esophagus, stomach, small intestine, colon). Our goal is early detection of difficult-to-diagnose cancers with poor prognosis, working toward integrated imaging diagnosis across the digestive organs.
Hepatobiliary-pancreatic
Gastrointestinal tract
AI that detects and segments tumor lesions from CT images across the liver, biliary tract, and pancreas in an integrated way. By analyzing the three organs together, it aims to provide efficient diagnostic support.
AI that detects and segments tumor lesions from CT images across the esophagus, stomach, small intestine, and colon, aiming for integrated diagnostic support across the entire digestive system together with the hepatobiliary-pancreatic organs.
AI diagnostic support systems for fractures and bone tumors using X-ray imaging. Our solutions support rapid diagnosis in emergency and primary care settings, streamlining triage to orthopedic specialists.
Fractures
Bone tumors
Detection of high-risk fractures including proximal femur fractures (common in elderly) and pediatric supracondylar humerus fractures.
AI that detects bone tumors from X-ray images, helping prevent missed lesions and enabling early detection and appropriate triage to specialists. We aim to cover all three categories: primary bone tumors (such as osteosarcoma and Ewing sarcoma, common in young people, as well as osteochondroma, enchondroma, osteoid osteoma, and giant cell tumor of bone), myeloma (common in people aged 40 and over), and bone metastases.
In neurology, we work on two solutions: supporting thrombolysis (t-PA) eligibility decisions in acute ischemic stroke, and interpretation support for findings identified in brain dock (screening) exams. From acute care to preventive screening, we broadly support the interpretation of brain MRI and CT.
End-to-end application supporting t-PA eligibility decisions for acute ischemic stroke patients. Integrates clinical checklists through to decision support, aiming to contribute to reducing Door-to-Needle Time.
AI solution supporting everything from detection of findings identified in brain dock exams through to patient explanation. Assists brain-MRI interpretation and enables early detection of asymptomatic abnormalities.