PV-iRT

Intelligent radiotherapy solution

PV-iRT is an intelligent solution specifically designed for radiotherapy. It combines cutting-edge artificial intelligence and imaging analysis technology to empower every radiotherapy process, providing cancer patients with more accurate treatment. The solution covers data management, image processing, AI auto-contouring, image fusion, manual contouring, custom AI model training, etc., providing professional and reliable tools for radiotherapy oncologists and physicists

Solutions

PVmed Contouring Software
Research Tool

iCurve: Auto Contouring

Auto-contouring of organs-at-risk as well as lymphatic drainage area based on the proprietary deep learning and machine learning technology

iFusion: Image Fusion

Fast rigid and deform-able fusion of CT, MR, PET-CT, CBCT, 4DCT and spectral CT images; Support transformation from CBCT/MR to CT images.

iLearning

Customized contouring models combining expert experience and AI algorithms, via adaptive learning

iDose

Intelligent dosimetric analysis and evaluation platform for radiation therapy

Deployment

These data may help to better understand the variability of technologies that prosthetic arms can provide.

Compatible with DICOM protocols and mainstream devices
Deployed within institution to ensure data safety
Supports multiple terminals and mobile devices

Auto contouring

Head & Neck CT

Head & Neck MR

Chest CT

Breast CT

Abdomen CT

Female Pelvic CT

Male Pelvic CT

Pelvic MR

Whole Scan
Structure List

Whole Scan
Structure List

Whole Scan
Structure List

Whole Scan
Structure List

Whole Scan
Structure List

Whole Scan
Structure List

Whole Scan
Structure List

Whole Scan
Structure List

Image Fusion

Software provides powerful and easy-to-use image fusion module to achieve more accurate contouring.

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Collaboration

PV-iRT as OEM product to empower our business partners in radiotherapy industry

PV-iSpectra
PV-iTherapy

PV-iSpectra: Spectral CT Comprehensive Solution

Spectral CT(multi-energy CT) is an advanced medical imaging technology. It captures data at different energy levels of X-rays, which allows it to generate multiple energy-specific images, enabling clearer differentiation of tissue types and abnormalities.

Synchronous contour-modification on multi-energy-level spectral CT sequences

Review and verification of image fusion result

PV-iTherapy: Online-Collaborative Adaptive Radiotherapy Solution

The quality of synthetic CT images, based on AI technology, has reached the level of CT-Sim, with artifacts effectively removed

The quality of synthetic CT images, based on AI technology, has reached the level of CT-Sim, with artifacts effectively removed

Contouring accuracy of critical organs for cervical cancer, including bladder, rectum, colon and small bowel, has been greatly optimized based on online CBCT/CT images

University of Michigan

University of Michigan

Harvard University

Harvard University

BGI

BGI

Sun Yat-sen University Cancer Center

Sun Yat-sen University Cancer Center

KINGMED

KINGMED

HIT Big Data Group

HIT Big Data Group

Shanghai University of Medicine and Health Sciences

Shanghai University of Medicine and Health Sciences

CEI Cloud

CEI Cloud

Advantages

Process

Accuracy is our top priority. The organ segmentation algorithm is developed based on internationally recognized clinical guidelines, combined with personalized inputs from clinical experts.

Driven by extensive patient data, our model undergoes refinement, always pursuing higher level of accuracy and generalization.

Authoritative Clinical Guidelines

From radiation oncology associations including RTOG and CRTOG as reference

Top Experts’ Experience

From multiple cancer centers are combined into model refinement

Continuing Polishing

Of contouring models based on clinical research data

Efficient

Auto-contouring of whole-body OARs completed within 5 minutes

Auto contouring of OARs of nasopharynx carcinoma saves over 95% of working time

Customizable

PV-iRT provides flexible and customizable contouring models, to align with the personal work experience of clinical users and meet individualized clinical needs.

01

Few-shots AI deep learning engine: training can be initiated with a minimum of 3 samples

02

Data stays within the hospital, ensuring data privacy and security

03

Intuitive user interface: user can train personal expert model effortlessly with just a few clicks