RSIP Participates in Vision Day
Yesterday our algorithm developers took a break from their regular duties to take part in vision day at Tel-Aviv University. It’s always great to meet our colleagues and
RSIP Vision Learns
Data and Annotation Challenges in Medical AI Development
David Menashe, Arie Rond, Ilya Kovler Introduction In recent years, artificial intelligence (AI) has revolutionized many fields and has had a major impact on our
Improved PCNL with Computer Vision
Larger stones in the kidney and proximal ureter need to be treated with PCNL (Percutaneous Nephrolithotomy), a minimally invasive urology procedure intended to remove them.
Super-Resolution in OCT images
OCT images are frequently used to demonstrate the retina and understand the different pathologies and decide the diagnostics and help with procedure planning. In medical
AI-Assisted Prostate Cancer Diagnosis
Prostate cancer is the second most prevalent cancer in men, affecting about 1 in 8 men during their lifetime. Often, patients will have an MRI
AI algorithms for Surgical Video Analysis
Surgical video analysis involves using artificial intelligence and machine learning algorithms to analyze surgical video footage. This practice, which includes both intraoperative and postoperative video
XPlan.AI by RSIP Vision – New AI-based 2D-to-3D Joint Reconstruction from X-ray Images
3D models of joints and bones are widely used for a large variety of orthopedic clinical purposes including preoperative planning, patient specific implant design, jig
Intra-op Prostate Guidance by RSIP Vision
Approximately one million prostate biopsies are performed each year in the United States to diagnose and monitor prostate cancer. Doctors commonly use transrectal ultrasound (TRUS)
IBD Scoring – Clario, GI Reviewers and RSIP Vision Team Up
Clario, GI Reviewers and RSIP Vision Team Up to Present a New AI Solution to Advance Clinical Trials for Inflammatory Bowel Diseases Innovative, human-level AI
Soft Tissue Tracking during Brain Surgeries
Most of the tissue handled by the surgeon (or by a robotic hand) during brain surgeries is flexible: With the obvious exception of bone, which
AI for Benign Prostatic Hyperplasia BPH
How can Artificial Intelligence benefit urology patients, in particular those affected by prostate BPH (Benign Prostatic Hyperplasia)? AI-based solutions for urology applications are under development
How Can AI Assist in Single-port Robotic Surgery?
The use by the surgical community of single-port as a surgical approach is increasing in frequency. A port is the entrance gate of the tools
AI-Assisted Brain Surgery
Brain surgeries are very complex: they need to be extremely accurate, since you want to spare healthy tissue; planning is very thorough, as the surgeon
PCNL – Planning and real-time navigation
Urolithiasis, or kidney stones, is a common pathology affecting nearly 10% of the population in the USA. Percutaneous Nephrolithotomy (PCNL) is a minimally invasive urology
Implementing AI to Improve PI-RADS Scoring
Prostate Cancer and PI-RADS scoring Prostate cancer is the most common male cancer in the USA. When diagnosed early, mortality rates are very low, therefore,
Tissue Sparing in Robotic Assisted Orthopedic Surgeries
Orthopedic surgeries such as hip or knee replacement are performed via an incision which often compromises the surrounding tissue. The assimilation of RAS into these
Procedural Planning in Urology
Challenges in Biopsies There are various types of urological cancers, the most common ones being prostate and kidney cancer. In cancer, early and accurate detection
Radiation Reduction in Robotic Assisted Surgeries (RAS) Using AI
Fluoroscopy is an extremely useful imaging tool in surgical procedures in orthopedics, cardiology, GI, etc. In some cases, it is used as a real-time modality
Hyperspectral Imaging for Robotic Assisted Surgery
Standard imaging techniques make use of the visible light spectrum. As is known, the visible light is divided into three bands – red, green, and
Image Analysis and Artificial Intelligence in Urology
Artificial intelligence (AI) and deep learning play an increasingly crucial role in medical imaging in general, and in the field of urology particularly. The applications of AI in urology are numerous, starting with accurate diagnosis (using image segmentation and abnormality detection), continuing with biopsy and operative procedures (using tools for assisted navigation and robotic guidance), and ending in treatment assessment (using tools similar to those used in diagnosis in order to assess the response to treatment).
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